Milestone1-2ORG.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rhgpM92PMCd-"
   },
   "source": [
    "# Milestone 1: FL Intra-company\n",
    "\n",
    "Train a single model in a federated way for each company. This way, we keep the privacy of the data for each user and measure the performance of the model compared to the besalines of individual subjects and company."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "rhgpM92PMCd-"
   },
   "source": [
    "# Scenario config with Flower\n",
    "\n",
    "Use of the 'simulation' module (version 0.18.0) which removes the scalability restrictions presented in previous versions\n",
    "\n",
    "It is necessary to install Flower with the 'simulation' extra"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "BXG21C3dLj6i",
    "outputId": "f60586a0-3fc5-4801-919d-01977224a39b",
    "tags": []
   },
   "outputs": [],
   "source": [
    "# !pip install -U flwr[\"simulation\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tQk9ZzCBMf9r"
   },
   "source": [
    "Libraries used"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "id": "oKvjox6uMkhj"
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import math\n",
    "\n",
    "# Make TensorFlow logs less verbose\n",
    "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\"\n",
    "\n",
    "import flwr as fl\n",
    "import tensorflow as tf\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from tensorflow.keras.utils import to_categorical\n",
    "\n",
    "from keras.models import Sequential\n",
    "from tensorflow.keras.layers import Dense, BatchNormalization\n",
    "from tensorflow.keras.optimizers import Adadelta\n",
    "\n",
    "from typing import Dict\n",
    "\n",
    "from flwr.common.logger import log\n",
    "from logging import INFO\n",
    "from csv import writer\n",
    "\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "30pJWfaTM_MC"
   },
   "source": [
    "Federated learning systems consist of a server and multiple clients.\n",
    "\n",
    "In Flower, we create clients by implementing subclasses of `flwr.client.Client` or `flwr.client.NumPyClient`.\n",
    "\n",
    "To implement the Flower client, we create a subclass of `flwr.client.NumPyClient` and implement the three methods `get_parameters`, `fit`, and `evaluate`:\n",
    "\n",
    "- `get_parameters`: Return the current local model parameters\n",
    "- `fit`: Receive model parameters from the server, train the model parameters on the local data, and return the (updated) model parameters to the server \n",
    "- `evaluate`: Received model parameters from the server, evaluate the model parameters on the local data, and return the evaluation result to the server\n",
    "\n",
    "We mentioned that our clients will use TensorFlow/Keras for the model training and evaluation. Keras models provide methods that make the implementation staightforward:\n",
    "- we can update the local model with server-provides parameters through `model.set_weights`\n",
    "- we can train/evaluate the model through `fit/evaluate`\n",
    "- we can get the updated model parameters through `model.get_weights`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "id": "vE3mqBs0NHZi"
   },
   "outputs": [],
   "source": [
    "class FlowerClient(fl.client.NumPyClient):\n",
    "    def __init__(self, cid, model, x_train, y_train, x_val, y_val) -> None:\n",
    "        self.cid = cid\n",
    "        self.model = model\n",
    "        self.x_train, self.y_train = x_train, y_train\n",
    "        self.x_val, self.y_val = x_val, y_val\n",
    "\n",
    "    def get_parameters(self):\n",
    "        return self.model.get_weights()\n",
    "\n",
    "    def fit(self, parameters, config):\n",
    "        self.model.set_weights(parameters)\n",
    "        \n",
    "        self.model.fit(self.x_train, self.y_train,\n",
    "                       epochs=int(config[\"epochs\"]),\n",
    "                       batch_size=32,\n",
    "                       verbose=0)\n",
    "        \n",
    "        return self.model.get_weights(), len(self.x_train), {}\n",
    "\n",
    "    def evaluate(self, parameters, config):\n",
    "        self.model.set_weights(parameters)\n",
    "        \n",
    "        loss, acc = self.model.evaluate(self.x_val, self.y_val, verbose=0)\n",
    "        \n",
    "        return loss, len(self.x_val), {\"accuracy\": acc, \"client\": self.cid}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our class `FlowerClient` defines how local training/evaluation will be performed and allows Flower to call the local training/evaluation through `fit` and `evaluate`. Each instance of `FlowerClient` represents a *single client* in our federated learning system. \n",
    "\n",
    "Federated learning systems have multiple clients, so each client will be represented by its own instance of `FlowerClient`.\n",
    "- Flower calls `FlowerClient.fit` on the respective instance when the server selects a particular client for training \n",
    "- (and `FlowerClient.evaluate` for evaluation).\n",
    "\n",
    "In this notebook, we want to simulate a federated learning system with 21 clients on a single machine. This means that the server and all 21 clients will live on a single machine and share resources such as CPU, GPU, and memory. Having 21 clients would mean having 21 instances of `FlowerClient` im memory and 21 GRCP conections. **Doing this on a single machine can quickly exhaust the available memory resources, even if only a subset of these clients participates in a single round of federated learning.**\n",
    "\n",
    "In addition to the regular capabilities where server and clients run on multiple machines, **Flower therefore provides special simulation capabilities that create `FlowerClient` instances only when they are actually necessary for training or evaluation**.\n",
    "\n",
    "**To enable the Flower framework to create clients when necessary, we need to implement a function called `client_fn` that creates a `FlowerClient` instance on demand**. Flower calls `client_fn` whenever it needs an instance of one particular client to call `fit` **or** `evaluate` (those instances are usually discarded after use).\n",
    "- Clients are identified by a client ID, or short `cid`. The `cid` can be used, for example, to load different local data partitions for each client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "''' Load data from a particular client '''\n",
    "def prepare_model_data(client_file):\n",
    "    df = pd.read_csv(client_file)\n",
    "    \n",
    "    train, test = train_test_split(df, test_size=0.30, random_state=42)\n",
    "    \n",
    "    X_train = train[['psd_delta', 'psd_theta', 'psd_alpha', 'psd_beta', 'psd_gamma','eog_blinks', 'eog_var']]\n",
    "    X_test = test[['psd_delta', 'psd_theta', 'psd_alpha', 'psd_beta', 'psd_gamma','eog_blinks', 'eog_var']]\n",
    "    y_train = train['y_class']\n",
    "    y_test = test['y_class']\n",
    "    \n",
    "    scaler = StandardScaler()\n",
    "\n",
    "    X_train = scaler.fit_transform(X_train)\n",
    "    X_test = scaler.transform(X_test)\n",
    "    \n",
    "    return X_train, X_test, y_train, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "id": "OtlBA2OFO0tf"
   },
   "outputs": [],
   "source": [
    "def client_fn(cid: str) -> fl.client.Client:\n",
    "    \n",
    "    # Model best hyperparameters (See notebook Milestone0-Optimization-Baseline)\n",
    "    neurons = 36\n",
    "    activation = \"relu\"\n",
    "    learning_rate = 0.180165\n",
    "    optimizer = Adadelta(learning_rate=learning_rate)\n",
    "    \n",
    "    input_shape = (7,)\n",
    "    \n",
    "    # Create model\n",
    "    model = Sequential()\n",
    "    \n",
    "    model.add(Dense(neurons, input_shape=input_shape, activation=activation))\n",
    "    \n",
    "    model.add(BatchNormalization())\n",
    "        \n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    model.add(Dense(neurons, activation=activation))\n",
    "    \n",
    "    model.add(Dense(1, activation='sigmoid'))\n",
    "    \n",
    "    model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])\n",
    "\n",
    "    # Load data partition\n",
    "    base_path = \"./data/horizontal/\"\n",
    "    path = f\"{base_path}company_{(int(cid)%2)+1}/client_{cid}.csv\"\n",
    "    \n",
    "    x_train_cid, x_val_cid, y_train_cid, y_val_cid = prepare_model_data(path)\n",
    "\n",
    "    # Create and return client\n",
    "    return FlowerClient(cid, model, x_train_cid, y_train_cid, x_val_cid, y_val_cid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6SVawWSgO48Q"
   },
   "source": [
    "We now have `FlowerClient` which defines client-side training and evaluation and `client_fn` which allows Flower to create `FlowerClient` instances whenever it needs to call `fit` or `evaluate` on one particular client.\n",
    "\n",
    "The next step is to define a custom strategy that will allow us to store aggregated weights, perform LOG tasks and to store the evaluation results for each round performed during the training process."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class SaveModelStrategy(fl.server.strategy.FedAvg):\n",
    "    def aggregate_fit(self, rnd, results, failures):\n",
    "        aggregated_weights = super().aggregate_fit(rnd, results, failures)\n",
    "            \n",
    "        return aggregated_weights\n",
    "\n",
    "    def aggregate_evaluate(self, rnd, results, failures):\n",
    "        super_result = super().aggregate_evaluate(rnd, results, failures)\n",
    "        \n",
    "        log(\n",
    "            INFO,\n",
    "            f\"round-{rnd}-EVALUATION\"\n",
    "        )\n",
    "        \n",
    "        accuracy = []\n",
    "        data = {}\n",
    "        for r in results:\n",
    "            acc = r[1].metrics[\"accuracy\"]\n",
    "            client = r[1].metrics[\"client\"]\n",
    "            data[client] = acc\n",
    "            accuracy.append(acc)\n",
    "        \n",
    "        df = pd.DataFrame(data, index=[0], columns=sorted(data.keys()))\n",
    "        df.to_csv(f\"./results/milestone1-company_{company}.csv\", mode='a', index=False, header=False)\n",
    "        \n",
    "        log(\n",
    "            INFO,\n",
    "            sorted(data.items())\n",
    "        )\n",
    "        \n",
    "        np.array(accuracy)\n",
    "        log(\n",
    "            INFO,\n",
    "            f\"Aggregated accuracy: {np.mean(accuracy)} +- {np.std(accuracy)}\"\n",
    "        )\n",
    "        \n",
    "        return super_result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "6SVawWSgO48Q"
   },
   "source": [
    "The last step is to start the actual simulation using `flwr.simulation.start_simulation`.\n",
    "\n",
    "The function `start_simulation` accepts a number of arguments, amongst them the `client_fn` used to create `FlowerClient` instances.\n",
    "- the clients IDs `clients_ids`\n",
    "- the number of rounds `num_rounds`\n",
    "- and the strategy. The strategy encapsulates the custom federated learning approach/algorithm that was implemented above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "collapsed": true,
    "id": "0Yxjysu5PM-A",
    "jupyter": {
     "outputs_hidden": true
    },
    "outputId": "cf5f1bab-0d94-4876-bd6a-cdb0652826ff",
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "INFO flower 2022-04-08 20:35:35,738 | app.py:144 | Ray initialized with resources: {'object_store_memory': 5705349120.0, 'GPU': 1.0, 'memory': 11410698240.0, 'CPU': 8.0, 'node:127.0.0.1': 1.0}\n",
      "INFO flower 2022-04-08 20:35:35,739 | app.py:153 | Starting Flower simulation running: {'num_rounds': 200}\n",
      "INFO flower 2022-04-08 20:35:35,740 | server.py:128 | Initializing global parameters\n",
      "INFO flower 2022-04-08 20:35:35,740 | server.py:327 | Requesting initial parameters from one random client\n",
      "INFO flower 2022-04-08 20:35:39,307 | server.py:330 | Received initial parameters from one random client\n",
      "INFO flower 2022-04-08 20:35:39,307 | server.py:130 | Evaluating initial parameters\n",
      "INFO flower 2022-04-08 20:35:39,308 | server.py:143 | FL starting\n",
      "DEBUG flower 2022-04-08 20:35:39,308 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:35:46,230 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:35:46,252 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:35:48,695 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:35:48,695 | 2092374713.py:15 | round-1-EVALUATION\n",
      "INFO flower 2022-04-08 20:35:48,699 | 2092374713.py:31 | [(2, 0.8078431487083435), (4, 0.4091816246509552), (6, 0.19767442345619202), (8, 0.7126436829566956), (10, 0.22519083321094513), (12, 0.3811475336551666), (14, 0.4124999940395355), (16, 0.3598484992980957), (18, 0.5140562057495117), (20, 0.7176470756530762)]\n",
      "INFO flower 2022-04-08 20:35:48,700 | 2092374713.py:37 | Aggregated accuracy: 0.47377330213785174 +- 0.1993157250179089\n",
      "DEBUG flower 2022-04-08 20:35:48,700 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:35:55,222 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:35:55,243 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:35:57,794 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:35:57,794 | 2092374713.py:15 | round-2-EVALUATION\n",
      "INFO flower 2022-04-08 20:35:57,797 | 2092374713.py:31 | [(2, 0.7058823704719543), (4, 0.6646706461906433), (6, 0.3294573724269867), (8, 0.5287356376647949), (10, 0.4122137427330017), (12, 0.7254098653793335), (14, 0.5583333373069763), (16, 0.5833333134651184), (18, 0.7550200819969177), (20, 0.7176470756530762)]\n",
      "INFO flower 2022-04-08 20:35:57,797 | 2092374713.py:37 | Aggregated accuracy: 0.5980703443288803 +- 0.13583273464943055\n",
      "DEBUG flower 2022-04-08 20:35:57,798 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:04,189 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:04,210 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:06,749 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:06,750 | 2092374713.py:15 | round-3-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:06,752 | 2092374713.py:31 | [(2, 0.6196078658103943), (4, 0.7485029697418213), (6, 0.6976743936538696), (8, 0.4597701132297516), (10, 0.5419847369194031), (12, 0.868852436542511), (14, 0.6458333134651184), (16, 0.7196969985961914), (18, 0.8152610659599304), (20, 0.6745098233222961)]\n",
      "INFO flower 2022-04-08 20:36:06,752 | 2092374713.py:37 | Aggregated accuracy: 0.6791693717241287 +- 0.11529480574687799\n",
      "DEBUG flower 2022-04-08 20:36:06,753 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:13,016 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:13,037 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:15,552 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:15,552 | 2092374713.py:15 | round-4-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:15,554 | 2092374713.py:31 | [(2, 0.48627451062202454), (4, 0.7904191613197327), (6, 0.7558139562606812), (8, 0.4214559495449066), (10, 0.6297709941864014), (12, 0.9098360538482666), (14, 0.6625000238418579), (16, 0.75), (18, 0.8112449645996094), (20, 0.6352941393852234)]\n",
      "INFO flower 2022-04-08 20:36:15,555 | 2092374713.py:37 | Aggregated accuracy: 0.6852609753608704 +- 0.14206182750429358\n",
      "DEBUG flower 2022-04-08 20:36:15,555 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:22,000 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:22,020 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:24,390 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:24,390 | 2092374713.py:15 | round-5-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:24,393 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.7944111824035645), (6, 0.7635658979415894), (8, 0.38697317242622375), (10, 0.6755725145339966), (12, 0.9057376980781555), (14, 0.6875), (16, 0.7613636255264282), (18, 0.8192771077156067), (20, 0.6274510025978088)]\n",
      "INFO flower 2022-04-08 20:36:24,393 | 2092374713.py:37 | Aggregated accuracy: 0.6868911027908325 +- 0.15476999943979833\n",
      "DEBUG flower 2022-04-08 20:36:24,394 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:30,781 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:30,802 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:33,369 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:33,369 | 2092374713.py:15 | round-6-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:33,372 | 2092374713.py:31 | [(2, 0.4313725531101227), (4, 0.7984032034873962), (6, 0.7790697813034058), (8, 0.38314175605773926), (10, 0.7061068415641785), (12, 0.8975409865379333), (14, 0.7041666507720947), (16, 0.7840909361839294), (18, 0.827309250831604), (20, 0.6235294342041016)]\n",
      "INFO flower 2022-04-08 20:36:33,372 | 2092374713.py:37 | Aggregated accuracy: 0.6934731394052506 +- 0.16008524224304055\n",
      "DEBUG flower 2022-04-08 20:36:33,373 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:39,863 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:39,883 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:42,450 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:42,451 | 2092374713.py:15 | round-7-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:42,453 | 2092374713.py:31 | [(2, 0.4313725531101227), (4, 0.7904191613197327), (6, 0.7751938104629517), (8, 0.37547892332077026), (10, 0.7137404680252075), (12, 0.8934426307678223), (14, 0.7041666507720947), (16, 0.7954545617103577), (18, 0.8192771077156067), (20, 0.6313725709915161)]\n",
      "INFO flower 2022-04-08 20:36:42,454 | 2092374713.py:37 | Aggregated accuracy: 0.6929918438196182 +- 0.16015235383660523\n",
      "DEBUG flower 2022-04-08 20:36:42,454 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:48,704 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:48,724 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:51,137 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:51,138 | 2092374713.py:15 | round-8-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:51,140 | 2092374713.py:31 | [(2, 0.4313725531101227), (4, 0.7924151420593262), (6, 0.7751938104629517), (8, 0.37547892332077026), (10, 0.7290076613426208), (12, 0.8975409865379333), (14, 0.7166666388511658), (16, 0.810606062412262), (18, 0.827309250831604), (20, 0.6352941393852234)]\n",
      "INFO flower 2022-04-08 20:36:51,141 | 2092374713.py:37 | Aggregated accuracy: 0.699088516831398 +- 0.16261329940900568\n",
      "DEBUG flower 2022-04-08 20:36:51,141 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:57,323 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:36:57,344 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:36:59,858 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:36:59,859 | 2092374713.py:15 | round-9-EVALUATION\n",
      "INFO flower 2022-04-08 20:36:59,861 | 2092374713.py:31 | [(2, 0.43529412150382996), (4, 0.802395224571228), (6, 0.7635658979415894), (8, 0.37547892332077026), (10, 0.732824444770813), (12, 0.9098360538482666), (14, 0.7083333134651184), (16, 0.8295454382896423), (18, 0.8473895788192749), (20, 0.6431372761726379)]\n",
      "INFO flower 2022-04-08 20:36:59,861 | 2092374713.py:37 | Aggregated accuracy: 0.7047800272703171 +- 0.16631211193963505\n",
      "DEBUG flower 2022-04-08 20:36:59,862 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:05,855 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:05,875 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:08,294 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:37:08,294 | 2092374713.py:15 | round-10-EVALUATION\n",
      "INFO flower 2022-04-08 20:37:08,296 | 2092374713.py:31 | [(2, 0.43529412150382996), (4, 0.8083832263946533), (6, 0.7441860437393188), (8, 0.37547892332077026), (10, 0.732824444770813), (12, 0.9098360538482666), (14, 0.7083333134651184), (16, 0.8295454382896423), (18, 0.8514056205749512), (20, 0.6431372761726379)]\n",
      "INFO flower 2022-04-08 20:37:08,297 | 2092374713.py:37 | Aggregated accuracy: 0.7038424462080002 +- 0.16644876908008385\n",
      "DEBUG flower 2022-04-08 20:37:08,297 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:14,278 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:14,298 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:16,584 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:37:16,585 | 2092374713.py:15 | round-11-EVALUATION\n",
      "INFO flower 2022-04-08 20:37:16,587 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8103792667388916), (6, 0.7441860437393188), (8, 0.37547892332077026), (10, 0.732824444770813), (12, 0.9139344096183777), (14, 0.7124999761581421), (16, 0.8295454382896423), (18, 0.8594377636909485), (20, 0.6431372761726379)]\n",
      "INFO flower 2022-04-08 20:37:16,588 | 2092374713.py:37 | Aggregated accuracy: 0.7060639232397079 +- 0.1671909323414296\n",
      "DEBUG flower 2022-04-08 20:37:16,588 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:23,033 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:23,053 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:25,598 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:37:25,598 | 2092374713.py:15 | round-12-EVALUATION\n",
      "INFO flower 2022-04-08 20:37:25,601 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8103792667388916), (6, 0.7325581312179565), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.9098360538482666), (14, 0.7041666507720947), (16, 0.8371211886405945), (18, 0.8634538054466248), (20, 0.6313725709915161)]\n",
      "INFO flower 2022-04-08 20:37:25,601 | 2092374713.py:37 | Aggregated accuracy: 0.7040208876132965 +- 0.16876617766249932\n",
      "DEBUG flower 2022-04-08 20:37:25,602 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:31,768 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:31,788 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:34,203 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:37:34,204 | 2092374713.py:15 | round-13-EVALUATION\n",
      "INFO flower 2022-04-08 20:37:34,206 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8123752474784851), (6, 0.6899224519729614), (8, 0.37931033968925476), (10, 0.732824444770813), (12, 0.9180327653884888), (14, 0.7041666507720947), (16, 0.8371211886405945), (18, 0.8714859485626221), (20, 0.6392157077789307)]\n",
      "INFO flower 2022-04-08 20:37:34,207 | 2092374713.py:37 | Aggregated accuracy: 0.7031513571739196 +- 0.1673287217226902\n",
      "DEBUG flower 2022-04-08 20:37:34,208 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:40,562 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:40,583 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:43,115 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:37:43,115 | 2092374713.py:15 | round-14-EVALUATION\n",
      "INFO flower 2022-04-08 20:37:43,118 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8223552703857422), (6, 0.6744186282157898), (8, 0.37931033968925476), (10, 0.7290076613426208), (12, 0.9180327653884888), (14, 0.7124999761581421), (16, 0.8371211886405945), (18, 0.8714859485626221), (20, 0.6431372761726379)]\n",
      "INFO flower 2022-04-08 20:37:43,118 | 2092374713.py:37 | Aggregated accuracy: 0.7038349449634552 +- 0.16742454225811024\n",
      "DEBUG flower 2022-04-08 20:37:43,119 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:49,498 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:49,519 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:52,174 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:37:52,175 | 2092374713.py:15 | round-15-EVALUATION\n",
      "INFO flower 2022-04-08 20:37:52,177 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8163672685623169), (6, 0.6782945990562439), (8, 0.37547892332077026), (10, 0.732824444770813), (12, 0.9262295365333557), (14, 0.7124999761581421), (16, 0.8446969985961914), (18, 0.8714859485626221), (20, 0.6470588445663452)]\n",
      "INFO flower 2022-04-08 20:37:52,178 | 2092374713.py:37 | Aggregated accuracy: 0.7048073798418045 +- 0.17048010692597454\n",
      "DEBUG flower 2022-04-08 20:37:52,178 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:37:58,898 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:37:58,918 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:01,341 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:01,342 | 2092374713.py:15 | round-16-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:01,344 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8203592896461487), (6, 0.6782945990562439), (8, 0.37164750695228577), (10, 0.732824444770813), (12, 0.9262295365333557), (14, 0.7124999761581421), (16, 0.8484848737716675), (18, 0.8714859485626221), (20, 0.6470588445663452)]\n",
      "INFO flower 2022-04-08 20:38:01,344 | 2092374713.py:37 | Aggregated accuracy: 0.7052022278308868 +- 0.1717999214405007\n",
      "DEBUG flower 2022-04-08 20:38:01,345 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:07,464 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:07,484 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:09,786 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:09,787 | 2092374713.py:15 | round-17-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:09,789 | 2092374713.py:31 | [(2, 0.43529412150382996), (4, 0.8163672685623169), (6, 0.6666666865348816), (8, 0.3639846742153168), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.7083333134651184), (16, 0.8484848737716675), (18, 0.8674699068069458), (20, 0.6392157077789307)]\n",
      "INFO flower 2022-04-08 20:38:09,790 | 2092374713.py:37 | Aggregated accuracy: 0.7016602456569672 +- 0.17497036277388311\n",
      "DEBUG flower 2022-04-08 20:38:09,790 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:15,894 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:15,914 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:18,759 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:18,759 | 2092374713.py:15 | round-18-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:18,762 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8203592896461487), (6, 0.6550387740135193), (8, 0.36781609058380127), (10, 0.7366412281990051), (12, 0.938524603843689), (14, 0.7083333134651184), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.6431372761726379)]\n",
      "INFO flower 2022-04-08 20:38:18,762 | 2092374713.py:37 | Aggregated accuracy: 0.7051937252283096 +- 0.17463030905113477\n",
      "DEBUG flower 2022-04-08 20:38:18,762 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:24,845 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:24,866 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:27,154 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:27,155 | 2092374713.py:15 | round-19-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:27,157 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8203592896461487), (6, 0.6589147448539734), (8, 0.3639846742153168), (10, 0.732824444770813), (12, 0.938524603843689), (14, 0.7041666507720947), (16, 0.8636363744735718), (18, 0.8714859485626221), (20, 0.6431372761726379)]\n",
      "INFO flower 2022-04-08 20:38:27,157 | 2092374713.py:37 | Aggregated accuracy: 0.7044092833995819 +- 0.1761453746403927\n",
      "DEBUG flower 2022-04-08 20:38:27,158 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:33,129 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:33,149 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:35,918 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:35,919 | 2092374713.py:15 | round-20-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:35,921 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8243513107299805), (6, 0.6395348906517029), (8, 0.3639846742153168), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.7041666507720947), (16, 0.8636363744735718), (18, 0.8634538054466248), (20, 0.6392157077789307)]\n",
      "INFO flower 2022-04-08 20:38:35,921 | 2092374713.py:37 | Aggregated accuracy: 0.7020777642726899 +- 0.17521329439788325\n",
      "DEBUG flower 2022-04-08 20:38:35,922 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:41,789 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:41,809 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:44,204 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:44,205 | 2092374713.py:15 | round-21-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:44,207 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8243513107299805), (6, 0.6356589198112488), (8, 0.3639846742153168), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7083333134651184), (16, 0.8636363744735718), (18, 0.8634538054466248), (20, 0.6392157077789307)]\n",
      "INFO flower 2022-04-08 20:38:44,208 | 2092374713.py:37 | Aggregated accuracy: 0.7017428278923035 +- 0.17642232656489473\n",
      "DEBUG flower 2022-04-08 20:38:44,208 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:50,282 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:50,303 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:52,611 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:38:52,612 | 2092374713.py:15 | round-22-EVALUATION\n",
      "INFO flower 2022-04-08 20:38:52,614 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8283433318138123), (6, 0.6782945990562439), (8, 0.3563218414783478), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.7124999761581421), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.6352941393852234)]\n",
      "INFO flower 2022-04-08 20:38:52,615 | 2092374713.py:37 | Aggregated accuracy: 0.7052529692649842 +- 0.17823072257811662\n",
      "DEBUG flower 2022-04-08 20:38:52,615 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:38:58,724 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:38:58,745 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:01,033 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:01,033 | 2092374713.py:15 | round-23-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:01,036 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8243513107299805), (6, 0.682170569896698), (8, 0.3524904251098633), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.7124999761581421), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.6352941393852234)]\n",
      "INFO flower 2022-04-08 20:39:01,036 | 2092374713.py:37 | Aggregated accuracy: 0.7052503794431686 +- 0.17808682590450342\n",
      "DEBUG flower 2022-04-08 20:39:01,037 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:07,326 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:07,346 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:09,843 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:09,844 | 2092374713.py:15 | round-24-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:09,846 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8243513107299805), (6, 0.6937984228134155), (8, 0.3524904251098633), (10, 0.7366412281990051), (12, 0.9426229596138), (14, 0.7124999761581421), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.6235294342041016)]\n",
      "INFO flower 2022-04-08 20:39:09,847 | 2092374713.py:37 | Aggregated accuracy: 0.7064098864793777 +- 0.17912802491541333\n",
      "DEBUG flower 2022-04-08 20:39:09,847 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:15,835 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:15,855 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:18,250 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:18,251 | 2092374713.py:15 | round-25-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:18,253 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8243513107299805), (6, 0.6860465407371521), (8, 0.3524904251098633), (10, 0.732824444770813), (12, 0.9426229596138), (14, 0.7041666507720947), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.6274510025978088)]\n",
      "INFO flower 2022-04-08 20:39:18,254 | 2092374713.py:37 | Aggregated accuracy: 0.7052040010690689 +- 0.1783838263284184\n",
      "DEBUG flower 2022-04-08 20:39:18,254 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:24,211 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:24,231 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:26,793 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:26,794 | 2092374713.py:15 | round-26-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:26,796 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8203592896461487), (6, 0.6550387740135193), (8, 0.3563218414783478), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7166666388511658), (16, 0.8598484992980957), (18, 0.8634538054466248), (20, 0.6274510025978088)]\n",
      "INFO flower 2022-04-08 20:39:26,796 | 2092374713.py:37 | Aggregated accuracy: 0.7021855592727662 +- 0.17662336450308355\n",
      "DEBUG flower 2022-04-08 20:39:26,797 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:32,746 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:32,767 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:35,184 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:35,185 | 2092374713.py:15 | round-27-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:35,187 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8203592896461487), (6, 0.6744186282157898), (8, 0.3601532578468323), (10, 0.7213740348815918), (12, 0.9426229596138), (14, 0.7124999761581421), (16, 0.8598484992980957), (18, 0.8674699068069458), (20, 0.6274510025978088)]\n",
      "INFO flower 2022-04-08 20:39:35,188 | 2092374713.py:37 | Aggregated accuracy: 0.7041099518537521 +- 0.175750041976264\n",
      "DEBUG flower 2022-04-08 20:39:35,188 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:41,599 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:41,619 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:43,957 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:43,958 | 2092374713.py:15 | round-28-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:43,960 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.6666666865348816), (8, 0.3563218414783478), (10, 0.7175572514533997), (12, 0.9426229596138), (14, 0.699999988079071), (16, 0.8560606241226196), (18, 0.8674699068069458), (20, 0.6235294342041016)]\n",
      "INFO flower 2022-04-08 20:39:43,961 | 2092374713.py:37 | Aggregated accuracy: 0.701532906293869 +- 0.17546680061687472\n",
      "DEBUG flower 2022-04-08 20:39:43,961 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:50,234 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:50,253 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:52,667 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:39:52,668 | 2092374713.py:15 | round-29-EVALUATION\n",
      "INFO flower 2022-04-08 20:39:52,670 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8203592896461487), (6, 0.682170569896698), (8, 0.3601532578468323), (10, 0.7213740348815918), (12, 0.9426229596138), (14, 0.7041666507720947), (16, 0.8560606241226196), (18, 0.8674699068069458), (20, 0.6117647290229797)]\n",
      "INFO flower 2022-04-08 20:39:52,671 | 2092374713.py:37 | Aggregated accuracy: 0.7024965554475784 +- 0.17547947977868375\n",
      "DEBUG flower 2022-04-08 20:39:52,671 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:39:58,752 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:39:58,773 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:01,241 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:01,242 | 2092374713.py:15 | round-30-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:01,244 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8203592896461487), (6, 0.7054263353347778), (8, 0.3601532578468323), (10, 0.7213740348815918), (12, 0.9426229596138), (14, 0.699999988079071), (16, 0.8560606241226196), (18, 0.8674699068069458), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:40:01,245 | 2092374713.py:37 | Aggregated accuracy: 0.7032289952039719 +- 0.17740305924051425\n",
      "DEBUG flower 2022-04-08 20:40:01,245 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:07,572 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:40:07,592 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:09,989 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:09,989 | 2092374713.py:15 | round-31-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:09,992 | 2092374713.py:31 | [(2, 0.43529412150382996), (4, 0.8203592896461487), (6, 0.7403100728988647), (8, 0.3448275923728943), (10, 0.7366412281990051), (12, 0.938524603843689), (14, 0.699999988079071), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.6117647290229797)]\n",
      "INFO flower 2022-04-08 20:40:09,992 | 2092374713.py:37 | Aggregated accuracy: 0.7058827906847001 +- 0.1824354383316992\n",
      "DEBUG flower 2022-04-08 20:40:09,993 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:16,105 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:40:16,125 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:18,756 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:18,757 | 2092374713.py:15 | round-32-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:18,759 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8223552703857422), (6, 0.7364341020584106), (8, 0.3448275923728943), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.699999988079071), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:40:18,759 | 2092374713.py:37 | Aggregated accuracy: 0.705715748667717 +- 0.18160251042492354\n",
      "DEBUG flower 2022-04-08 20:40:18,760 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:24,831 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:40:24,851 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:27,329 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:27,330 | 2092374713.py:15 | round-33-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:27,332 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8223552703857422), (6, 0.7170542478561401), (8, 0.3486590087413788), (10, 0.7290076613426208), (12, 0.9426229596138), (14, 0.699999988079071), (16, 0.8598484992980957), (18, 0.8674699068069458), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:40:27,333 | 2092374713.py:37 | Aggregated accuracy: 0.7045841097831727 +- 0.18024548176257016\n",
      "DEBUG flower 2022-04-08 20:40:27,333 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:33,812 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:40:33,832 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:36,648 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:36,648 | 2092374713.py:15 | round-34-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:36,651 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8203592896461487), (6, 0.7286821603775024), (8, 0.3448275923728943), (10, 0.7251908183097839), (12, 0.938524603843689), (14, 0.699999988079071), (16, 0.8598484992980957), (18, 0.8674699068069458), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:40:36,651 | 2092374713.py:37 | Aggregated accuracy: 0.704764798283577 +- 0.17984541835193799\n",
      "DEBUG flower 2022-04-08 20:40:36,652 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:42,759 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:40:42,779 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:45,305 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:45,305 | 2092374713.py:15 | round-35-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:45,308 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8203592896461487), (6, 0.6782945990562439), (8, 0.3486590087413788), (10, 0.7213740348815918), (12, 0.9426229596138), (14, 0.699999988079071), (16, 0.8598484992980957), (18, 0.8714859485626221), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:40:45,308 | 2092374713.py:37 | Aggregated accuracy: 0.7013232588768006 +- 0.17884183967026798\n",
      "DEBUG flower 2022-04-08 20:40:45,309 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:51,618 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:40:51,639 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:40:54,212 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:40:54,212 | 2092374713.py:15 | round-36-EVALUATION\n",
      "INFO flower 2022-04-08 20:40:54,214 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8243513107299805), (6, 0.7015503644943237), (8, 0.3486590087413788), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7041666507720947), (16, 0.8598484992980957), (18, 0.8674699068069458), (20, 0.6117647290229797)]\n",
      "INFO flower 2022-04-08 20:40:54,215 | 2092374713.py:37 | Aggregated accuracy: 0.704052621126175 +- 0.17880603140677312\n",
      "DEBUG flower 2022-04-08 20:40:54,215 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:00,279 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:00,300 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:02,817 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:02,817 | 2092374713.py:15 | round-37-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:02,819 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8243513107299805), (6, 0.7170542478561401), (8, 0.3524904251098633), (10, 0.7251908183097839), (12, 0.938524603843689), (14, 0.7041666507720947), (16, 0.8674242496490479), (18, 0.8674699068069458), (20, 0.6117647290229797)]\n",
      "INFO flower 2022-04-08 20:41:02,820 | 2092374713.py:37 | Aggregated accuracy: 0.7055495768785477 +- 0.1793311731569931\n",
      "DEBUG flower 2022-04-08 20:41:02,820 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:09,120 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:09,141 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:11,457 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:11,458 | 2092374713.py:15 | round-38-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:11,461 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8223552703857422), (6, 0.6976743936538696), (8, 0.3524904251098633), (10, 0.7175572514533997), (12, 0.9467213153839111), (14, 0.7083333134651184), (16, 0.8636363744735718), (18, 0.8674699068069458), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:41:11,461 | 2092374713.py:37 | Aggregated accuracy: 0.7042904943227768 +- 0.17909403879888752\n",
      "DEBUG flower 2022-04-08 20:41:11,462 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:17,460 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:17,480 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:19,887 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:19,888 | 2092374713.py:15 | round-39-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:19,890 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8243513107299805), (6, 0.7325581312179565), (8, 0.3524904251098633), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.7041666507720947), (16, 0.875), (18, 0.8674699068069458), (20, 0.6078431606292725)]\n",
      "INFO flower 2022-04-08 20:41:19,891 | 2092374713.py:37 | Aggregated accuracy: 0.7082392245531082 +- 0.17987077172641236\n",
      "DEBUG flower 2022-04-08 20:41:19,891 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:26,169 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:26,190 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:28,927 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:28,928 | 2092374713.py:15 | round-40-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:28,931 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8223552703857422), (6, 0.713178277015686), (8, 0.3563218414783478), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7083333134651184), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.615686297416687)]\n",
      "INFO flower 2022-04-08 20:41:28,931 | 2092374713.py:37 | Aggregated accuracy: 0.7081465601921082 +- 0.17944679061395838\n",
      "DEBUG flower 2022-04-08 20:41:28,932 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:35,131 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:35,152 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:37,573 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:37,574 | 2092374713.py:15 | round-41-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:37,576 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.826347291469574), (6, 0.7286821603775024), (8, 0.3601532578468323), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7124999761581421), (16, 0.875), (18, 0.8714859485626221), (20, 0.6039215922355652)]\n",
      "INFO flower 2022-04-08 20:41:37,577 | 2092374713.py:37 | Aggregated accuracy: 0.7096884399652481 +- 0.17952003669204172\n",
      "DEBUG flower 2022-04-08 20:41:37,578 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:44,084 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:44,105 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:46,448 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:46,448 | 2092374713.py:15 | round-42-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:46,451 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8243513107299805), (6, 0.7054263353347778), (8, 0.3601532578468323), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7166666388511658), (16, 0.875), (18, 0.8755019903182983), (20, 0.6117647290229797)]\n",
      "INFO flower 2022-04-08 20:41:46,451 | 2092374713.py:37 | Aggregated accuracy: 0.7095678359270096 +- 0.17920415388783323\n",
      "DEBUG flower 2022-04-08 20:41:46,451 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:52,696 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:41:52,717 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:41:55,281 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:41:55,282 | 2092374713.py:15 | round-43-EVALUATION\n",
      "INFO flower 2022-04-08 20:41:55,284 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8243513107299805), (6, 0.7209302186965942), (8, 0.3563218414783478), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7208333611488342), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.5960784554481506)]\n",
      "INFO flower 2022-04-08 20:41:55,285 | 2092374713.py:37 | Aggregated accuracy: 0.7087583184242249 +- 0.18093269756476432\n",
      "DEBUG flower 2022-04-08 20:41:55,285 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:01,561 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:01,581 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:04,137 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:04,137 | 2092374713.py:15 | round-44-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:04,140 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.826347291469574), (6, 0.713178277015686), (8, 0.3639846742153168), (10, 0.7213740348815918), (12, 0.9467213153839111), (14, 0.7166666388511658), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.6039215922355652)]\n",
      "INFO flower 2022-04-08 20:42:04,140 | 2092374713.py:37 | Aggregated accuracy: 0.7097235918045044 +- 0.17991312202283286\n",
      "DEBUG flower 2022-04-08 20:42:04,141 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:10,396 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:10,416 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:12,774 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:12,774 | 2092374713.py:15 | round-45-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:12,777 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.826347291469574), (6, 0.713178277015686), (8, 0.3639846742153168), (10, 0.7213740348815918), (12, 0.9467213153839111), (14, 0.7208333611488342), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5960784554481506)]\n",
      "INFO flower 2022-04-08 20:42:12,777 | 2092374713.py:37 | Aggregated accuracy: 0.7093559503555298 +- 0.18041129070402936\n",
      "DEBUG flower 2022-04-08 20:42:12,778 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:18,942 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:18,963 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:21,240 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:21,240 | 2092374713.py:15 | round-46-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:21,243 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.826347291469574), (6, 0.7596899271011353), (8, 0.3601532578468323), (10, 0.7290076613426208), (12, 0.9426229596138), (14, 0.7166666388511658), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:42:21,243 | 2092374713.py:37 | Aggregated accuracy: 0.7119922012090683 +- 0.1829700723493694\n",
      "DEBUG flower 2022-04-08 20:42:21,244 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:27,259 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:27,278 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:29,690 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:29,690 | 2092374713.py:15 | round-47-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:29,693 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8223552703857422), (6, 0.7829457521438599), (8, 0.3601532578468323), (10, 0.7366412281990051), (12, 0.938524603843689), (14, 0.7041666507720947), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:42:29,693 | 2092374713.py:37 | Aggregated accuracy: 0.7126299470663071 +- 0.18364273067440492\n",
      "DEBUG flower 2022-04-08 20:42:29,694 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:35,667 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:35,687 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:38,225 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:38,226 | 2092374713.py:15 | round-48-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:38,228 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8243513107299805), (6, 0.7751938104629517), (8, 0.3639846742153168), (10, 0.732824444770813), (12, 0.938524603843689), (14, 0.7083333134651184), (16, 0.8863636255264282), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:42:38,229 | 2092374713.py:37 | Aggregated accuracy: 0.7128512740135193 +- 0.18304415071986166\n",
      "DEBUG flower 2022-04-08 20:42:38,229 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:44,556 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:44,576 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:47,047 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:47,047 | 2092374713.py:15 | round-49-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:47,050 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8243513107299805), (6, 0.7751938104629517), (8, 0.3639846742153168), (10, 0.732824444770813), (12, 0.938524603843689), (14, 0.7083333134651184), (16, 0.8863636255264282), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:42:47,050 | 2092374713.py:37 | Aggregated accuracy: 0.7128512740135193 +- 0.18304415071986163\n",
      "DEBUG flower 2022-04-08 20:42:47,051 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:53,367 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:42:53,387 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:42:55,728 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:42:55,728 | 2092374713.py:15 | round-50-EVALUATION\n",
      "INFO flower 2022-04-08 20:42:55,731 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.8223552703857422), (6, 0.786821722984314), (8, 0.3639846742153168), (10, 0.732824444770813), (12, 0.938524603843689), (14, 0.7041666507720947), (16, 0.8863636255264282), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:42:55,731 | 2092374713.py:37 | Aggregated accuracy: 0.7133977949619293 +- 0.18337053675362355\n",
      "DEBUG flower 2022-04-08 20:42:55,732 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:01,819 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:01,840 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:04,699 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:04,700 | 2092374713.py:15 | round-51-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:04,702 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8283433318138123), (6, 0.7829457521438599), (8, 0.36781609058380127), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.7083333134651184), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:43:04,703 | 2092374713.py:37 | Aggregated accuracy: 0.7140405029058456 +- 0.18186336175508963\n",
      "DEBUG flower 2022-04-08 20:43:04,703 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:10,868 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:10,888 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:13,432 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:13,433 | 2092374713.py:15 | round-52-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:13,435 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8283433318138123), (6, 0.7674418687820435), (8, 0.37931033968925476), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7166666388511658), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:43:13,436 | 2092374713.py:37 | Aggregated accuracy: 0.7153030157089233 +- 0.1795873408078101\n",
      "DEBUG flower 2022-04-08 20:43:13,436 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:19,905 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:19,926 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:22,264 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:22,264 | 2092374713.py:15 | round-53-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:22,267 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8283433318138123), (6, 0.7054263353347778), (8, 0.39080458879470825), (10, 0.7175572514533997), (12, 0.9426229596138), (14, 0.7291666865348816), (16, 0.8787878751754761), (18, 0.8674699068069458), (20, 0.6000000238418579)]\n",
      "INFO flower 2022-04-08 20:43:22,267 | 2092374713.py:37 | Aggregated accuracy: 0.7119002491235733 +- 0.17288415490647727\n",
      "DEBUG flower 2022-04-08 20:43:22,268 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:28,662 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:28,683 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:31,083 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:31,084 | 2092374713.py:15 | round-54-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:31,086 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8303393125534058), (6, 0.7674418687820435), (8, 0.38314175605773926), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7208333611488342), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:43:31,087 | 2092374713.py:37 | Aggregated accuracy: 0.7158925920724869 +- 0.17848153044704293\n",
      "DEBUG flower 2022-04-08 20:43:31,088 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:37,622 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:37,646 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:40,573 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:40,573 | 2092374713.py:15 | round-55-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:40,576 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8283433318138123), (6, 0.7286821603775024), (8, 0.39080458879470825), (10, 0.7175572514533997), (12, 0.9426229596138), (14, 0.7250000238418579), (16, 0.8787878751754761), (18, 0.8674699068069458), (20, 0.6000000238418579)]\n",
      "INFO flower 2022-04-08 20:43:40,576 | 2092374713.py:37 | Aggregated accuracy: 0.7138091653585434 +- 0.17290635204865323\n",
      "DEBUG flower 2022-04-08 20:43:40,577 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:47,559 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:47,580 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:50,329 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:50,330 | 2092374713.py:15 | round-56-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:50,332 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8303393125534058), (6, 0.7441860437393188), (8, 0.38314175605773926), (10, 0.7290076613426208), (12, 0.9426229596138), (14, 0.7124999761581421), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:43:50,333 | 2092374713.py:37 | Aggregated accuracy: 0.7146572440862655 +- 0.17753437729093932\n",
      "DEBUG flower 2022-04-08 20:43:50,333 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:56,976 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:43:56,996 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:43:59,431 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:43:59,432 | 2092374713.py:15 | round-57-EVALUATION\n",
      "INFO flower 2022-04-08 20:43:59,434 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.826347291469574), (6, 0.748062014579773), (8, 0.38314175605773926), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7208333611488342), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:43:59,434 | 2092374713.py:37 | Aggregated accuracy: 0.7155071288347244 +- 0.17757321483699448\n",
      "DEBUG flower 2022-04-08 20:43:59,435 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:06,249 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:44:06,270 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:08,782 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:44:08,783 | 2092374713.py:15 | round-58-EVALUATION\n",
      "INFO flower 2022-04-08 20:44:08,785 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.826347291469574), (6, 0.7325581312179565), (8, 0.38314175605773926), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7250000238418579), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:44:08,786 | 2092374713.py:37 | Aggregated accuracy: 0.7147655636072159 +- 0.17708643103634367\n",
      "DEBUG flower 2022-04-08 20:44:08,786 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:15,444 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:44:15,465 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:18,090 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:44:18,090 | 2092374713.py:15 | round-59-EVALUATION\n",
      "INFO flower 2022-04-08 20:44:18,093 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8283433318138123), (6, 0.7209302186965942), (8, 0.37931033968925476), (10, 0.7290076613426208), (12, 0.9467213153839111), (14, 0.7250000238418579), (16, 0.8901515007019043), (18, 0.8674699068069458), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:44:18,094 | 2092374713.py:37 | Aggregated accuracy: 0.7133993148803711 +- 0.17752621650570652\n",
      "DEBUG flower 2022-04-08 20:44:18,094 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:24,860 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:44:24,881 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:27,450 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:44:27,451 | 2092374713.py:15 | round-60-EVALUATION\n",
      "INFO flower 2022-04-08 20:44:27,453 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8283433318138123), (6, 0.7713178396224976), (8, 0.37547892332077026), (10, 0.7290076613426208), (12, 0.9426229596138), (14, 0.7208333611488342), (16, 0.8901515007019043), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:44:27,454 | 2092374713.py:37 | Aggregated accuracy: 0.7168551713228226 +- 0.18041901220547737\n",
      "DEBUG flower 2022-04-08 20:44:27,454 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:33,765 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:44:33,785 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:36,281 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:44:36,281 | 2092374713.py:15 | round-61-EVALUATION\n",
      "INFO flower 2022-04-08 20:44:36,284 | 2092374713.py:31 | [(2, 0.4431372582912445), (4, 0.8283433318138123), (6, 0.7945736646652222), (8, 0.3601532578468323), (10, 0.7404580116271973), (12, 0.938524603843689), (14, 0.7124999761581421), (16, 0.8901515007019043), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:44:36,284 | 2092374713.py:37 | Aggregated accuracy: 0.7159814208745956 +- 0.1858067665275874\n",
      "DEBUG flower 2022-04-08 20:44:36,285 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:42,756 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:44:42,778 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:45,312 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:44:45,313 | 2092374713.py:15 | round-62-EVALUATION\n",
      "INFO flower 2022-04-08 20:44:45,315 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8283433318138123), (6, 0.7906976938247681), (8, 0.36781609058380127), (10, 0.7404580116271973), (12, 0.938524603843689), (14, 0.7208333611488342), (16, 0.8901515007019043), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:44:45,316 | 2092374713.py:37 | Aggregated accuracy: 0.7175856024026871 +- 0.18360660463063866\n",
      "DEBUG flower 2022-04-08 20:44:45,316 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:52,142 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:44:52,163 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:44:55,080 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:44:55,081 | 2092374713.py:15 | round-63-EVALUATION\n",
      "INFO flower 2022-04-08 20:44:55,084 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.826347291469574), (6, 0.7558139562606812), (8, 0.37931033968925476), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7291666865348816), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:44:55,084 | 2092374713.py:37 | Aggregated accuracy: 0.7159305214881897 +- 0.17826137972960363\n",
      "DEBUG flower 2022-04-08 20:44:55,085 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:02,109 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:02,131 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:04,789 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:45:04,789 | 2092374713.py:15 | round-64-EVALUATION\n",
      "INFO flower 2022-04-08 20:45:04,792 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.7054263353347778), (8, 0.38697317242622375), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.737500011920929), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5921568870544434)]\n",
      "INFO flower 2022-04-08 20:45:04,793 | 2092374713.py:37 | Aggregated accuracy: 0.7140706360340119 +- 0.17532926396449386\n",
      "DEBUG flower 2022-04-08 20:45:04,793 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:11,823 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:11,843 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:14,481 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:45:14,481 | 2092374713.py:15 | round-65-EVALUATION\n",
      "INFO flower 2022-04-08 20:45:14,484 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8303393125534058), (6, 0.748062014579773), (8, 0.37931033968925476), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7333333492279053), (16, 0.8901515007019043), (18, 0.8755019903182983), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:45:14,486 | 2092374713.py:37 | Aggregated accuracy: 0.7175669491291046 +- 0.17841048440914592\n",
      "DEBUG flower 2022-04-08 20:45:14,486 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:21,394 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:21,415 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:24,189 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:45:24,190 | 2092374713.py:15 | round-66-EVALUATION\n",
      "INFO flower 2022-04-08 20:45:24,192 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8283433318138123), (6, 0.7325581312179565), (8, 0.37931033968925476), (10, 0.732824444770813), (12, 0.9467213153839111), (14, 0.7416666746139526), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:45:24,193 | 2092374713.py:37 | Aggregated accuracy: 0.7174042105674744 +- 0.17758830314432564\n",
      "DEBUG flower 2022-04-08 20:45:24,193 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:31,080 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:31,101 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:33,836 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:45:33,836 | 2092374713.py:15 | round-67-EVALUATION\n",
      "INFO flower 2022-04-08 20:45:33,839 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8283433318138123), (6, 0.748062014579773), (8, 0.37547892332077026), (10, 0.7404580116271973), (12, 0.9426229596138), (14, 0.7333333492279053), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:45:33,840 | 2092374713.py:37 | Aggregated accuracy: 0.716915175318718 +- 0.17887508202115293\n",
      "DEBUG flower 2022-04-08 20:45:33,840 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:40,731 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:40,753 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:43,396 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:45:43,397 | 2092374713.py:15 | round-68-EVALUATION\n",
      "INFO flower 2022-04-08 20:45:43,399 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.832335352897644), (6, 0.7790697813034058), (8, 0.37164750695228577), (10, 0.7442747950553894), (12, 0.9426229596138), (14, 0.7291666865348816), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:45:43,399 | 2092374713.py:37 | Aggregated accuracy: 0.7196048676967621 +- 0.18121920504188643\n",
      "DEBUG flower 2022-04-08 20:45:43,400 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:50,428 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:50,448 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:53,055 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:45:53,056 | 2092374713.py:15 | round-69-EVALUATION\n",
      "INFO flower 2022-04-08 20:45:53,058 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8283433318138123), (6, 0.7751938104629517), (8, 0.37931033968925476), (10, 0.7404580116271973), (12, 0.9426229596138), (14, 0.7333333492279053), (16, 0.8901515007019043), (18, 0.8674699068069458), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:45:53,059 | 2092374713.py:37 | Aggregated accuracy: 0.7200020492076874 +- 0.17790130343029398\n",
      "DEBUG flower 2022-04-08 20:45:53,060 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:45:59,972 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:45:59,993 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:02,780 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:46:02,781 | 2092374713.py:15 | round-70-EVALUATION\n",
      "INFO flower 2022-04-08 20:46:02,783 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.826347291469574), (6, 0.7403100728988647), (8, 0.38697317242622375), (10, 0.732824444770813), (12, 0.9426229596138), (14, 0.737500011920929), (16, 0.8863636255264282), (18, 0.8714859485626221), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:46:02,784 | 2092374713.py:37 | Aggregated accuracy: 0.7171486377716064 +- 0.17517776051596803\n",
      "DEBUG flower 2022-04-08 20:46:02,784 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:09,643 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:46:09,664 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:12,270 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:46:12,270 | 2092374713.py:15 | round-71-EVALUATION\n",
      "INFO flower 2022-04-08 20:46:12,273 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8303393125534058), (6, 0.7984496355056763), (8, 0.37547892332077026), (10, 0.7480915784835815), (12, 0.9426229596138), (14, 0.7291666865348816), (16, 0.8863636255264282), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:46:12,273 | 2092374713.py:37 | Aggregated accuracy: 0.7233073562383652 +- 0.17968708552494014\n",
      "DEBUG flower 2022-04-08 20:46:12,274 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:19,383 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:46:19,404 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:22,062 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:46:22,062 | 2092374713.py:15 | round-72-EVALUATION\n",
      "INFO flower 2022-04-08 20:46:22,065 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.832335352897644), (6, 0.786821722984314), (8, 0.37164750695228577), (10, 0.7442747950553894), (12, 0.9426229596138), (14, 0.7250000238418579), (16, 0.8863636255264282), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:46:22,066 | 2092374713.py:37 | Aggregated accuracy: 0.7207705259323121 +- 0.18034393003413293\n",
      "DEBUG flower 2022-04-08 20:46:22,066 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:29,170 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:46:29,190 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:31,948 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:46:31,949 | 2092374713.py:15 | round-73-EVALUATION\n",
      "INFO flower 2022-04-08 20:46:31,951 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8283433318138123), (6, 0.751937985420227), (8, 0.39846742153167725), (10, 0.7404580116271973), (12, 0.9426229596138), (14, 0.7333333492279053), (16, 0.8825757503509521), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:46:31,952 | 2092374713.py:37 | Aggregated accuracy: 0.7200299650430679 +- 0.17337204397929631\n",
      "DEBUG flower 2022-04-08 20:46:31,952 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:38,719 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:46:38,740 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:41,387 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:46:41,388 | 2092374713.py:15 | round-74-EVALUATION\n",
      "INFO flower 2022-04-08 20:46:41,390 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8303393125534058), (6, 0.7829457521438599), (8, 0.37164750695228577), (10, 0.7480915784835815), (12, 0.9426229596138), (14, 0.7291666865348816), (16, 0.8825757503509521), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:46:41,391 | 2092374713.py:37 | Aggregated accuracy: 0.7209950387477875 +- 0.17949665743919924\n",
      "DEBUG flower 2022-04-08 20:46:41,391 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:48,504 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:46:48,525 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:51,264 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:46:51,265 | 2092374713.py:15 | round-75-EVALUATION\n",
      "INFO flower 2022-04-08 20:46:51,267 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8243513107299805), (6, 0.7403100728988647), (8, 0.38314175605773926), (10, 0.7442747950553894), (12, 0.9426229596138), (14, 0.737500011920929), (16, 0.8825757503509521), (18, 0.8755019903182983), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:46:51,268 | 2092374713.py:37 | Aggregated accuracy: 0.7177337497472763 +- 0.17617687032170345\n",
      "DEBUG flower 2022-04-08 20:46:51,269 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:46:58,243 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:46:58,264 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:01,033 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:01,033 | 2092374713.py:15 | round-76-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:01,036 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8223552703857422), (6, 0.682170569896698), (8, 0.40613025426864624), (10, 0.7290076613426208), (12, 0.9426229596138), (14, 0.737500011920929), (16, 0.875), (18, 0.8755019903182983), (20, 0.5960784554481506)]\n",
      "INFO flower 2022-04-08 20:47:01,036 | 2092374713.py:37 | Aggregated accuracy: 0.7140876978635788 +- 0.168478056620634\n",
      "DEBUG flower 2022-04-08 20:47:01,037 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:07,900 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:47:07,920 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:10,500 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:10,501 | 2092374713.py:15 | round-77-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:10,503 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8283433318138123), (6, 0.751937985420227), (8, 0.37931033968925476), (10, 0.7442747950553894), (12, 0.938524603843689), (14, 0.7333333492279053), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:47:10,504 | 2092374713.py:37 | Aggregated accuracy: 0.7176978647708893 +- 0.17551208569548016\n",
      "DEBUG flower 2022-04-08 20:47:10,504 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:17,574 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:47:17,596 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:20,251 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:20,251 | 2092374713.py:15 | round-78-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:20,254 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.826347291469574), (6, 0.751937985420227), (8, 0.37931033968925476), (10, 0.7442747950553894), (12, 0.9426229596138), (14, 0.737500011920929), (16, 0.8825757503509521), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:47:20,254 | 2092374713.py:37 | Aggregated accuracy: 0.7183208405971527 +- 0.17751329481260186\n",
      "DEBUG flower 2022-04-08 20:47:20,255 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:27,155 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:47:27,177 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:29,935 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:29,935 | 2092374713.py:15 | round-79-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:29,938 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8283433318138123), (6, 0.7829457521438599), (8, 0.36781609058380127), (10, 0.7519084215164185), (12, 0.938524603843689), (14, 0.7333333492279053), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:47:29,938 | 2092374713.py:37 | Aggregated accuracy: 0.720422026515007 +- 0.17937214840900179\n",
      "DEBUG flower 2022-04-08 20:47:29,939 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:36,873 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:47:36,894 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:39,530 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:39,531 | 2092374713.py:15 | round-80-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:39,534 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8303393125534058), (6, 0.7713178396224976), (8, 0.36781609058380127), (10, 0.7480915784835815), (12, 0.938524603843689), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:47:39,534 | 2092374713.py:37 | Aggregated accuracy: 0.7195183247327804 +- 0.17969861968669354\n",
      "DEBUG flower 2022-04-08 20:47:39,535 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:46,539 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:47:46,560 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:49,190 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:49,190 | 2092374713.py:15 | round-81-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:49,193 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8283433318138123), (6, 0.8100775480270386), (8, 0.3639846742153168), (10, 0.7480915784835815), (12, 0.938524603843689), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:47:49,193 | 2092374713.py:37 | Aggregated accuracy: 0.7216256380081176 +- 0.18211747882259308\n",
      "DEBUG flower 2022-04-08 20:47:49,194 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:56,062 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:47:56,083 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:47:58,884 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:47:58,885 | 2092374713.py:15 | round-82-EVALUATION\n",
      "INFO flower 2022-04-08 20:47:58,887 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8283433318138123), (6, 0.7984496355056763), (8, 0.3639846742153168), (10, 0.7442747950553894), (12, 0.938524603843689), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:47:58,888 | 2092374713.py:37 | Aggregated accuracy: 0.7216837525367736 +- 0.18129691087318325\n",
      "DEBUG flower 2022-04-08 20:47:58,888 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:05,786 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:48:05,806 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:08,403 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:48:08,404 | 2092374713.py:15 | round-83-EVALUATION\n",
      "INFO flower 2022-04-08 20:48:08,406 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.826347291469574), (6, 0.7635658979415894), (8, 0.37547892332077026), (10, 0.7442747950553894), (12, 0.9344262480735779), (14, 0.737500011920929), (16, 0.8787878751754761), (18, 0.8795180916786194), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:48:08,407 | 2092374713.py:37 | Aggregated accuracy: 0.7190879553556442 +- 0.1766398782428901\n",
      "DEBUG flower 2022-04-08 20:48:08,407 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:15,600 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:48:15,621 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:18,189 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:48:18,189 | 2092374713.py:15 | round-84-EVALUATION\n",
      "INFO flower 2022-04-08 20:48:18,192 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.826347291469574), (6, 0.8217054009437561), (8, 0.3639846742153168), (10, 0.7442747950553894), (12, 0.938524603843689), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:48:18,192 | 2092374713.py:37 | Aggregated accuracy: 0.7218149840831757 +- 0.18287556551432096\n",
      "DEBUG flower 2022-04-08 20:48:18,192 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:25,154 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:48:25,175 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:27,976 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:48:27,977 | 2092374713.py:15 | round-85-EVALUATION\n",
      "INFO flower 2022-04-08 20:48:27,979 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8283433318138123), (6, 0.7829457521438599), (8, 0.36781609058380127), (10, 0.7442747950553894), (12, 0.938524603843689), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8795180916786194), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:48:27,979 | 2092374713.py:37 | Aggregated accuracy: 0.7201092928647995 +- 0.18055080280173144\n",
      "DEBUG flower 2022-04-08 20:48:27,980 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:34,861 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:48:34,882 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:37,569 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:48:37,569 | 2092374713.py:15 | round-86-EVALUATION\n",
      "INFO flower 2022-04-08 20:48:37,572 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8303393125534058), (6, 0.8100775480270386), (8, 0.3639846742153168), (10, 0.7442747950553894), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8674699068069458), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:48:37,572 | 2092374713.py:37 | Aggregated accuracy: 0.7198478043079376 +- 0.18225270545981007\n",
      "DEBUG flower 2022-04-08 20:48:37,573 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:44,632 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:48:44,653 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:47,298 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:48:47,298 | 2092374713.py:15 | round-87-EVALUATION\n",
      "INFO flower 2022-04-08 20:48:47,302 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.826347291469574), (6, 0.8410852551460266), (8, 0.3639846742153168), (10, 0.7442747950553894), (12, 0.938524603843689), (14, 0.7458333373069763), (16, 0.875), (18, 0.8674699068069458), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:48:47,302 | 2092374713.py:37 | Aggregated accuracy: 0.7229970872402192 +- 0.18423605191628056\n",
      "DEBUG flower 2022-04-08 20:48:47,303 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:54,389 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:48:54,410 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:48:57,282 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:48:57,282 | 2092374713.py:15 | round-88-EVALUATION\n",
      "INFO flower 2022-04-08 20:48:57,285 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.826347291469574), (6, 0.7713178396224976), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.938524603843689), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:48:57,285 | 2092374713.py:37 | Aggregated accuracy: 0.7191461265087128 +- 0.1777509581095614\n",
      "DEBUG flower 2022-04-08 20:48:57,286 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:04,166 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:49:04,186 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:06,799 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:49:06,799 | 2092374713.py:15 | round-89-EVALUATION\n",
      "INFO flower 2022-04-08 20:49:06,802 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8243513107299805), (6, 0.7674418687820435), (8, 0.37547892332077026), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8795180916786194), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:49:06,802 | 2092374713.py:37 | Aggregated accuracy: 0.7189432948827743 +- 0.17754381926747115\n",
      "DEBUG flower 2022-04-08 20:49:06,803 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:13,894 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:49:13,914 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:16,495 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:49:16,495 | 2092374713.py:15 | round-90-EVALUATION\n",
      "INFO flower 2022-04-08 20:49:16,497 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8243513107299805), (6, 0.7713178396224976), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:49:16,498 | 2092374713.py:37 | Aggregated accuracy: 0.7189382970333099 +- 0.17747900984714288\n",
      "DEBUG flower 2022-04-08 20:49:16,499 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:23,363 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:49:23,384 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:26,184 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:49:26,184 | 2092374713.py:15 | round-91-EVALUATION\n",
      "INFO flower 2022-04-08 20:49:26,186 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8283433318138123), (6, 0.8062015771865845), (8, 0.3486590087413788), (10, 0.7442747950553894), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8674699068069458), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:49:26,187 | 2092374713.py:37 | Aggregated accuracy: 0.7165783107280731 +- 0.18487467589961182\n",
      "DEBUG flower 2022-04-08 20:49:26,187 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:33,118 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:49:33,139 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:35,738 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:49:35,739 | 2092374713.py:15 | round-92-EVALUATION\n",
      "INFO flower 2022-04-08 20:49:35,741 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8243513107299805), (6, 0.8023256063461304), (8, 0.37547892332077026), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:49:35,742 | 2092374713.py:37 | Aggregated accuracy: 0.7192777425050736 +- 0.17860315759750173\n",
      "DEBUG flower 2022-04-08 20:49:35,742 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:42,854 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:49:42,876 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:45,487 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:49:45,488 | 2092374713.py:15 | round-93-EVALUATION\n",
      "INFO flower 2022-04-08 20:49:45,491 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.826347291469574), (6, 0.8100775480270386), (8, 0.36781609058380127), (10, 0.7442747950553894), (12, 0.938524603843689), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:49:45,491 | 2092374713.py:37 | Aggregated accuracy: 0.7198856085538864 +- 0.18144108874048412\n",
      "DEBUG flower 2022-04-08 20:49:45,492 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:52,431 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:49:52,451 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:49:55,227 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:49:55,227 | 2092374713.py:15 | round-94-EVALUATION\n",
      "INFO flower 2022-04-08 20:49:55,231 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8243513107299805), (6, 0.7596899271011353), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.875), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:49:55,231 | 2092374713.py:37 | Aggregated accuracy: 0.716587895154953 +- 0.17732467605752203\n",
      "DEBUG flower 2022-04-08 20:49:55,232 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:02,088 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:50:02,108 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:04,733 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:50:04,733 | 2092374713.py:15 | round-95-EVALUATION\n",
      "INFO flower 2022-04-08 20:50:04,736 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8203592896461487), (6, 0.748062014579773), (8, 0.37164750695228577), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.75), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:50:04,736 | 2092374713.py:37 | Aggregated accuracy: 0.7154909253120423 +- 0.17603273764464744\n",
      "DEBUG flower 2022-04-08 20:50:04,737 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:11,769 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:50:11,790 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:14,383 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:50:14,384 | 2092374713.py:15 | round-96-EVALUATION\n",
      "INFO flower 2022-04-08 20:50:14,386 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.826347291469574), (6, 0.7286821603775024), (8, 0.39080458879470825), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:50:14,387 | 2092374713.py:37 | Aggregated accuracy: 0.7156309515237809 +- 0.1703770844067696\n",
      "DEBUG flower 2022-04-08 20:50:14,387 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:21,328 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:50:21,349 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:24,112 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:50:24,112 | 2092374713.py:15 | round-97-EVALUATION\n",
      "INFO flower 2022-04-08 20:50:24,115 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8243513107299805), (6, 0.786821722984314), (8, 0.37547892332077026), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:50:24,115 | 2092374713.py:37 | Aggregated accuracy: 0.7185070842504502 +- 0.17675210239897446\n",
      "DEBUG flower 2022-04-08 20:50:24,116 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:31,033 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:50:31,054 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:33,697 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:50:33,698 | 2092374713.py:15 | round-98-EVALUATION\n",
      "INFO flower 2022-04-08 20:50:33,700 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.826347291469574), (6, 0.7713178396224976), (8, 0.37164750695228577), (10, 0.732824444770813), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:50:33,701 | 2092374713.py:37 | Aggregated accuracy: 0.7167565047740936 +- 0.17454662649164432\n",
      "DEBUG flower 2022-04-08 20:50:33,701 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:40,729 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:50:40,750 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:43,314 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:50:43,315 | 2092374713.py:15 | round-99-EVALUATION\n",
      "INFO flower 2022-04-08 20:50:43,317 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8223552703857422), (6, 0.7596899271011353), (8, 0.37931033968925476), (10, 0.7290076613426208), (12, 0.9303278923034668), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:50:43,317 | 2092374713.py:37 | Aggregated accuracy: 0.7163973867893219 +- 0.17308428794618794\n",
      "DEBUG flower 2022-04-08 20:50:43,318 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:50,320 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:50:50,342 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:50:53,144 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:50:53,145 | 2092374713.py:15 | round-100-EVALUATION\n",
      "INFO flower 2022-04-08 20:50:53,148 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8223552703857422), (6, 0.7403100728988647), (8, 0.39463600516319275), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:50:53,149 | 2092374713.py:37 | Aggregated accuracy: 0.717580896615982 +- 0.17026743305962566\n",
      "DEBUG flower 2022-04-08 20:50:53,149 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:00,168 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:00,188 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:02,793 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:51:02,794 | 2092374713.py:15 | round-101-EVALUATION\n",
      "INFO flower 2022-04-08 20:51:02,796 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8183632493019104), (6, 0.7751938104629517), (8, 0.37931033968925476), (10, 0.7251908183097839), (12, 0.9344262480735779), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:51:02,797 | 2092374713.py:37 | Aggregated accuracy: 0.7155669212341309 +- 0.1748633564376283\n",
      "DEBUG flower 2022-04-08 20:51:02,797 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:09,695 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:09,716 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:12,485 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:51:12,485 | 2092374713.py:15 | round-102-EVALUATION\n",
      "INFO flower 2022-04-08 20:51:12,487 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.7945736646652222), (8, 0.3524904251098633), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:51:12,488 | 2092374713.py:37 | Aggregated accuracy: 0.7151775926351547 +- 0.18186203310254692\n",
      "DEBUG flower 2022-04-08 20:51:12,488 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:19,363 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:19,384 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:22,178 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:51:22,178 | 2092374713.py:15 | round-103-EVALUATION\n",
      "INFO flower 2022-04-08 20:51:22,181 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8203592896461487), (6, 0.7790697813034058), (8, 0.37164750695228577), (10, 0.7290076613426208), (12, 0.938524603843689), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:51:22,181 | 2092374713.py:37 | Aggregated accuracy: 0.7174048483371734 +- 0.17716123107197668\n",
      "DEBUG flower 2022-04-08 20:51:22,181 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:29,057 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:29,077 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:31,752 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:51:31,753 | 2092374713.py:15 | round-104-EVALUATION\n",
      "INFO flower 2022-04-08 20:51:31,755 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7596899271011353), (8, 0.37547892332077026), (10, 0.7251908183097839), (12, 0.9344262480735779), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:51:31,756 | 2092374713.py:37 | Aggregated accuracy: 0.7162198990583419 +- 0.17421202343964795\n",
      "DEBUG flower 2022-04-08 20:51:31,756 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:38,735 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:38,756 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:41,363 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:51:41,364 | 2092374713.py:15 | round-105-EVALUATION\n",
      "INFO flower 2022-04-08 20:51:41,366 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8283433318138123), (6, 0.8372092843055725), (8, 0.3448275923728943), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8674242496490479), (18, 0.8714859485626221), (20, 0.5490196347236633)]\n",
      "INFO flower 2022-04-08 20:51:41,367 | 2092374713.py:37 | Aggregated accuracy: 0.7165419489145279 +- 0.1879369537634357\n",
      "DEBUG flower 2022-04-08 20:51:41,367 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:48,322 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:48,343 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:51,112 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:51:51,113 | 2092374713.py:15 | round-106-EVALUATION\n",
      "INFO flower 2022-04-08 20:51:51,115 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.826347291469574), (6, 0.8023256063461304), (8, 0.3486590087413788), (10, 0.7442747950553894), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8714859485626221), (20, 0.5647059082984924)]\n",
      "INFO flower 2022-04-08 20:51:51,116 | 2092374713.py:37 | Aggregated accuracy: 0.715566211938858 +- 0.18413599294803884\n",
      "DEBUG flower 2022-04-08 20:51:51,116 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:51:58,038 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:51:58,059 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:00,721 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:00,722 | 2092374713.py:15 | round-107-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:00,724 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.826347291469574), (6, 0.7790697813034058), (8, 0.3524904251098633), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.875), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:52:00,725 | 2092374713.py:37 | Aggregated accuracy: 0.7151989549398422 +- 0.18210273940771768\n",
      "DEBUG flower 2022-04-08 20:52:00,725 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:07,622 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:52:07,643 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:10,402 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:10,402 | 2092374713.py:15 | round-108-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:10,405 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.826347291469574), (6, 0.7093023061752319), (8, 0.3601532578468323), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:52:10,405 | 2092374713.py:37 | Aggregated accuracy: 0.7122012346982955 +- 0.17666576816137827\n",
      "DEBUG flower 2022-04-08 20:52:10,406 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:17,288 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:52:17,309 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:20,103 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:20,104 | 2092374713.py:15 | round-109-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:20,106 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8223552703857422), (6, 0.748062014579773), (8, 0.3563218414783478), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:52:20,107 | 2092374713.py:37 | Aggregated accuracy: 0.7141183912754059 +- 0.1788610179965397\n",
      "DEBUG flower 2022-04-08 20:52:20,107 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:26,939 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:52:26,960 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:29,621 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:29,622 | 2092374713.py:15 | round-110-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:29,624 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7403100728988647), (8, 0.39080458879470825), (10, 0.7251908183097839), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8674242496490479), (18, 0.8835341334342957), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 20:52:29,625 | 2092374713.py:37 | Aggregated accuracy: 0.7162539631128311 +- 0.17098020304552036\n",
      "DEBUG flower 2022-04-08 20:52:29,625 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:36,570 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:52:36,591 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:39,429 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:39,430 | 2092374713.py:15 | round-111-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:39,432 | 2092374713.py:31 | [(2, 0.48627451062202454), (4, 0.8223552703857422), (6, 0.713178277015686), (8, 0.40613025426864624), (10, 0.7213740348815918), (12, 0.9344262480735779), (14, 0.7333333492279053), (16, 0.8674242496490479), (18, 0.8835341334342957), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:52:39,432 | 2092374713.py:37 | Aggregated accuracy: 0.7156265646219253 +- 0.1659732584027075\n",
      "DEBUG flower 2022-04-08 20:52:39,433 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:46,290 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:52:46,311 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:48,974 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:48,975 | 2092374713.py:15 | round-112-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:48,977 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8203592896461487), (6, 0.7558139562606812), (8, 0.37931033968925476), (10, 0.7290076613426208), (12, 0.9344262480735779), (14, 0.7458333373069763), (16, 0.8674242496490479), (18, 0.8875501751899719), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:52:48,978 | 2092374713.py:37 | Aggregated accuracy: 0.7158940970897675 +- 0.17598554865273894\n",
      "DEBUG flower 2022-04-08 20:52:48,978 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:56,189 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:52:56,210 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:52:58,916 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:52:58,917 | 2092374713.py:15 | round-113-EVALUATION\n",
      "INFO flower 2022-04-08 20:52:58,919 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8183632493019104), (6, 0.786821722984314), (8, 0.3601532578468323), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:52:58,921 | 2092374713.py:37 | Aggregated accuracy: 0.7160308867692947 +- 0.18036058337291996\n",
      "DEBUG flower 2022-04-08 20:52:58,922 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:05,808 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:53:05,829 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:08,577 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:53:08,577 | 2092374713.py:15 | round-114-EVALUATION\n",
      "INFO flower 2022-04-08 20:53:08,579 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8243513107299805), (6, 0.8023256063461304), (8, 0.3524904251098633), (10, 0.7442747950553894), (12, 0.9344262480735779), (14, 0.737500011920929), (16, 0.8674242496490479), (18, 0.8755019903182983), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:53:08,580 | 2092374713.py:37 | Aggregated accuracy: 0.7177510350942612 +- 0.18204062236892107\n",
      "DEBUG flower 2022-04-08 20:53:08,581 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:15,533 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:53:15,554 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:18,187 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:53:18,188 | 2092374713.py:15 | round-115-EVALUATION\n",
      "INFO flower 2022-04-08 20:53:18,190 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8243513107299805), (6, 0.7984496355056763), (8, 0.3524904251098633), (10, 0.7442747950553894), (12, 0.9344262480735779), (14, 0.737500011920929), (16, 0.8674242496490479), (18, 0.8755019903182983), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:53:18,190 | 2092374713.py:37 | Aggregated accuracy: 0.7173634380102157 +- 0.18186417613581005\n",
      "DEBUG flower 2022-04-08 20:53:18,191 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:25,229 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:53:25,250 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:27,844 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:53:27,845 | 2092374713.py:15 | round-116-EVALUATION\n",
      "INFO flower 2022-04-08 20:53:27,848 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8183632493019104), (6, 0.7829457521438599), (8, 0.36781609058380127), (10, 0.7290076613426208), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:53:27,848 | 2092374713.py:37 | Aggregated accuracy: 0.7160383731126785 +- 0.1783266540675183\n",
      "DEBUG flower 2022-04-08 20:53:27,849 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:34,760 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:53:34,781 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:37,630 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:53:37,631 | 2092374713.py:15 | round-117-EVALUATION\n",
      "INFO flower 2022-04-08 20:53:37,633 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8243513107299805), (6, 0.7906976938247681), (8, 0.3486590087413788), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7333333492279053), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:53:37,633 | 2092374713.py:37 | Aggregated accuracy: 0.7162005245685578 +- 0.18225543844952777\n",
      "DEBUG flower 2022-04-08 20:53:37,634 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:44,519 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:53:44,540 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:47,162 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:53:47,163 | 2092374713.py:15 | round-118-EVALUATION\n",
      "INFO flower 2022-04-08 20:53:47,165 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8243513107299805), (6, 0.7906976938247681), (8, 0.3524904251098633), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7291666865348816), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5647059082984924)]\n",
      "INFO flower 2022-04-08 20:53:47,166 | 2092374713.py:37 | Aggregated accuracy: 0.7153826862573623 +- 0.181857372508191\n",
      "DEBUG flower 2022-04-08 20:53:47,166 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:54,127 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:53:54,148 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:53:56,957 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:53:56,957 | 2092374713.py:15 | round-119-EVALUATION\n",
      "INFO flower 2022-04-08 20:53:56,960 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8183632493019104), (6, 0.7751938104629517), (8, 0.3639846742153168), (10, 0.7290076613426208), (12, 0.9344262480735779), (14, 0.7333333492279053), (16, 0.8674242496490479), (18, 0.8835341334342957), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:53:56,961 | 2092374713.py:37 | Aggregated accuracy: 0.7136639952659607 +- 0.17968743045170027\n",
      "DEBUG flower 2022-04-08 20:53:56,962 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:03,865 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:54:03,886 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:06,527 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:54:06,527 | 2092374713.py:15 | round-120-EVALUATION\n",
      "INFO flower 2022-04-08 20:54:06,530 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.786821722984314), (8, 0.3601532578468323), (10, 0.732824444770813), (12, 0.9344262480735779), (14, 0.7291666865348816), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:54:06,530 | 2092374713.py:37 | Aggregated accuracy: 0.7151905685663223 +- 0.18010772475124112\n",
      "DEBUG flower 2022-04-08 20:54:06,531 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:13,585 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:54:13,605 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:16,278 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:54:16,278 | 2092374713.py:15 | round-121-EVALUATION\n",
      "INFO flower 2022-04-08 20:54:16,280 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8243513107299805), (6, 0.8062015771865845), (8, 0.3563218414783478), (10, 0.732824444770813), (12, 0.9344262480735779), (14, 0.7291666865348816), (16, 0.8674242496490479), (18, 0.8755019903182983), (20, 0.5647059082984924)]\n",
      "INFO flower 2022-04-08 20:54:16,281 | 2092374713.py:37 | Aggregated accuracy: 0.7153669357299804 +- 0.18242951658786513\n",
      "DEBUG flower 2022-04-08 20:54:16,282 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:23,239 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:54:23,260 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:26,076 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:54:26,077 | 2092374713.py:15 | round-122-EVALUATION\n",
      "INFO flower 2022-04-08 20:54:26,079 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8203592896461487), (6, 0.7325581312179565), (8, 0.39080458879470825), (10, 0.7251908183097839), (12, 0.9303278923034668), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:54:26,080 | 2092374713.py:37 | Aggregated accuracy: 0.7130853325128556 +- 0.17236185395246725\n",
      "DEBUG flower 2022-04-08 20:54:26,081 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:33,027 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:54:33,048 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:35,682 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:54:35,682 | 2092374713.py:15 | round-123-EVALUATION\n",
      "INFO flower 2022-04-08 20:54:35,685 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7209302186965942), (8, 0.39080458879470825), (10, 0.7251908183097839), (12, 0.9303278923034668), (14, 0.7458333373069763), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 20:54:35,686 | 2092374713.py:37 | Aggregated accuracy: 0.7135290473699569 +- 0.17026202643584679\n",
      "DEBUG flower 2022-04-08 20:54:35,686 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:42,573 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:54:42,594 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:45,416 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:54:45,416 | 2092374713.py:15 | round-124-EVALUATION\n",
      "INFO flower 2022-04-08 20:54:45,418 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8183632493019104), (6, 0.7286821603775024), (8, 0.39846742153167725), (10, 0.7251908183097839), (12, 0.9303278923034668), (14, 0.7416666746139526), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5882353186607361)]\n",
      "INFO flower 2022-04-08 20:54:45,419 | 2092374713.py:37 | Aggregated accuracy: 0.714431431889534 +- 0.16915782973346496\n",
      "DEBUG flower 2022-04-08 20:54:45,419 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:52,472 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:54:52,493 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:54:55,368 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:54:55,369 | 2092374713.py:15 | round-125-EVALUATION\n",
      "INFO flower 2022-04-08 20:54:55,371 | 2092374713.py:31 | [(2, 0.4901960790157318), (4, 0.8163672685623169), (6, 0.6395348906517029), (8, 0.4137931168079376), (10, 0.7213740348815918), (12, 0.9303278923034668), (14, 0.7291666865348816), (16, 0.875), (18, 0.8795180916786194), (20, 0.6000000238418579)]\n",
      "INFO flower 2022-04-08 20:54:55,372 | 2092374713.py:37 | Aggregated accuracy: 0.7095278084278107 +- 0.164143799142318\n",
      "DEBUG flower 2022-04-08 20:54:55,372 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:02,377 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:55:02,398 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:05,015 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:55:05,016 | 2092374713.py:15 | round-126-EVALUATION\n",
      "INFO flower 2022-04-08 20:55:05,018 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8183632493019104), (6, 0.7209302186965942), (8, 0.40229883790016174), (10, 0.7251908183097839), (12, 0.9303278923034668), (14, 0.7416666746139526), (16, 0.875), (18, 0.8755019903182983), (20, 0.5921568870544434)]\n",
      "INFO flower 2022-04-08 20:55:05,018 | 2092374713.py:37 | Aggregated accuracy: 0.7155946373939515 +- 0.16732170454914988\n",
      "DEBUG flower 2022-04-08 20:55:05,019 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:11,970 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:55:11,991 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:14,805 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:55:14,805 | 2092374713.py:15 | round-127-EVALUATION\n",
      "INFO flower 2022-04-08 20:55:14,808 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8183632493019104), (6, 0.7403100728988647), (8, 0.37164750695228577), (10, 0.7290076613426208), (12, 0.9344262480735779), (14, 0.7458333373069763), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:55:14,808 | 2092374713.py:37 | Aggregated accuracy: 0.7125612437725067 +- 0.1771564414011466\n",
      "DEBUG flower 2022-04-08 20:55:14,809 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:21,692 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:55:21,713 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:24,389 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:55:24,390 | 2092374713.py:15 | round-128-EVALUATION\n",
      "INFO flower 2022-04-08 20:55:24,392 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8183632493019104), (6, 0.7170542478561401), (8, 0.39463600516319275), (10, 0.7213740348815918), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 20:55:24,393 | 2092374713.py:37 | Aggregated accuracy: 0.7109106838703155 +- 0.17037004627843064\n",
      "DEBUG flower 2022-04-08 20:55:24,393 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:31,464 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:55:31,485 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:34,176 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:55:34,177 | 2092374713.py:15 | round-129-EVALUATION\n",
      "INFO flower 2022-04-08 20:55:34,179 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8163672685623169), (6, 0.7325581312179565), (8, 0.39080458879470825), (10, 0.7290076613426208), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:55:34,180 | 2092374713.py:37 | Aggregated accuracy: 0.7126645177602768 +- 0.17095616424308874\n",
      "DEBUG flower 2022-04-08 20:55:34,181 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:41,077 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:55:41,098 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:43,712 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:55:43,712 | 2092374713.py:15 | round-130-EVALUATION\n",
      "INFO flower 2022-04-08 20:55:43,715 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.826347291469574), (6, 0.8100775480270386), (8, 0.3601532578468323), (10, 0.7366412281990051), (12, 0.9303278923034668), (14, 0.7333333492279053), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5490196347236633)]\n",
      "INFO flower 2022-04-08 20:55:43,715 | 2092374713.py:37 | Aggregated accuracy: 0.7155587643384933 +- 0.18330383897340838\n",
      "DEBUG flower 2022-04-08 20:55:43,716 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:50,690 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:55:50,711 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:55:53,550 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:55:53,551 | 2092374713.py:15 | round-131-EVALUATION\n",
      "INFO flower 2022-04-08 20:55:53,554 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8243513107299805), (6, 0.8294573426246643), (8, 0.3563218414783478), (10, 0.7480915784835815), (12, 0.9262295365333557), (14, 0.7291666865348816), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5372549295425415)]\n",
      "INFO flower 2022-04-08 20:55:53,554 | 2092374713.py:37 | Aggregated accuracy: 0.7152489304542542 +- 0.1868230912841427\n",
      "DEBUG flower 2022-04-08 20:55:53,555 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:00,524 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:00,544 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:03,246 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:56:03,246 | 2092374713.py:15 | round-132-EVALUATION\n",
      "INFO flower 2022-04-08 20:56:03,249 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8283433318138123), (6, 0.8023256063461304), (8, 0.3601532578468323), (10, 0.7442747950553894), (12, 0.9344262480735779), (14, 0.7333333492279053), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5490196347236633)]\n",
      "INFO flower 2022-04-08 20:56:03,250 | 2092374713.py:37 | Aggregated accuracy: 0.7169406801462174 +- 0.182559023324924\n",
      "DEBUG flower 2022-04-08 20:56:03,250 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:10,206 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:10,227 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:12,989 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:56:12,990 | 2092374713.py:15 | round-133-EVALUATION\n",
      "INFO flower 2022-04-08 20:56:12,993 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.826347291469574), (6, 0.8023256063461304), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.737500011920929), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 20:56:12,994 | 2092374713.py:37 | Aggregated accuracy: 0.7183176457881928 +- 0.17983509243502616\n",
      "DEBUG flower 2022-04-08 20:56:12,994 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:19,930 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:19,951 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:22,601 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:56:22,602 | 2092374713.py:15 | round-134-EVALUATION\n",
      "INFO flower 2022-04-08 20:56:22,604 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.826347291469574), (6, 0.8333333134651184), (8, 0.3448275923728943), (10, 0.7480915784835815), (12, 0.9262295365333557), (14, 0.7291666865348816), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5411764979362488)]\n",
      "INFO flower 2022-04-08 20:56:22,605 | 2092374713.py:37 | Aggregated accuracy: 0.7162553280591964 +- 0.18744964126933675\n",
      "DEBUG flower 2022-04-08 20:56:22,606 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:29,680 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:29,700 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:32,342 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:56:32,343 | 2092374713.py:15 | round-135-EVALUATION\n",
      "INFO flower 2022-04-08 20:56:32,345 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8203592896461487), (6, 0.7751938104629517), (8, 0.37931033968925476), (10, 0.732824444770813), (12, 0.9344262480735779), (14, 0.7458333373069763), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:56:32,346 | 2092374713.py:37 | Aggregated accuracy: 0.716626238822937 +- 0.17624420392418969\n",
      "DEBUG flower 2022-04-08 20:56:32,346 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:39,238 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:39,259 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:42,036 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:56:42,037 | 2092374713.py:15 | round-136-EVALUATION\n",
      "INFO flower 2022-04-08 20:56:42,039 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8243513107299805), (6, 0.8062015771865845), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.7291666865348816), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5490196347236633)]\n",
      "INFO flower 2022-04-08 20:56:42,039 | 2092374713.py:37 | Aggregated accuracy: 0.7160860061645508 +- 0.18079016960719324\n",
      "DEBUG flower 2022-04-08 20:56:42,040 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:49,015 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:49,037 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:51,712 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:56:51,713 | 2092374713.py:15 | round-137-EVALUATION\n",
      "INFO flower 2022-04-08 20:56:51,716 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8223552703857422), (6, 0.7945736646652222), (8, 0.37931033968925476), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.7333333492279053), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 20:56:51,717 | 2092374713.py:37 | Aggregated accuracy: 0.7159347176551819 +- 0.17935357729781481\n",
      "DEBUG flower 2022-04-08 20:56:51,717 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:56:58,775 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:56:58,796 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:01,593 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:57:01,594 | 2092374713.py:15 | round-138-EVALUATION\n",
      "INFO flower 2022-04-08 20:57:01,596 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8243513107299805), (6, 0.7906976938247681), (8, 0.37164750695228577), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7291666865348816), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 20:57:01,597 | 2092374713.py:37 | Aggregated accuracy: 0.7149454534053803 +- 0.18076621069431842\n",
      "DEBUG flower 2022-04-08 20:57:01,597 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:08,548 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:57:08,569 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:11,211 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:57:11,211 | 2092374713.py:15 | round-139-EVALUATION\n",
      "INFO flower 2022-04-08 20:57:11,214 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8223552703857422), (6, 0.8100775480270386), (8, 0.37164750695228577), (10, 0.7442747950553894), (12, 0.9303278923034668), (14, 0.7250000238418579), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 20:57:11,214 | 2092374713.py:37 | Aggregated accuracy: 0.7146703839302063 +- 0.18293447754797143\n",
      "DEBUG flower 2022-04-08 20:57:11,215 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:18,303 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:57:18,324 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:20,942 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:57:20,943 | 2092374713.py:15 | round-140-EVALUATION\n",
      "INFO flower 2022-04-08 20:57:20,946 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8183632493019104), (6, 0.7713178396224976), (8, 0.39080458879470825), (10, 0.7404580116271973), (12, 0.9344262480735779), (14, 0.7416666746139526), (16, 0.8674242496490479), (18, 0.8795180916786194), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 20:57:20,946 | 2092374713.py:37 | Aggregated accuracy: 0.716358682513237 +- 0.17532433855948934\n",
      "DEBUG flower 2022-04-08 20:57:20,947 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:27,921 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:57:27,943 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:30,725 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:57:30,725 | 2092374713.py:15 | round-141-EVALUATION\n",
      "INFO flower 2022-04-08 20:57:30,728 | 2092374713.py:31 | [(2, 0.48627451062202454), (4, 0.8183632493019104), (6, 0.7248061895370483), (8, 0.40229883790016174), (10, 0.7290076613426208), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:57:30,728 | 2092374713.py:37 | Aggregated accuracy: 0.7143919944763184 +- 0.16719162388005746\n",
      "DEBUG flower 2022-04-08 20:57:30,729 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:37,616 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:57:37,638 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:40,250 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:57:40,251 | 2092374713.py:15 | round-142-EVALUATION\n",
      "INFO flower 2022-04-08 20:57:40,253 | 2092374713.py:31 | [(2, 0.48235294222831726), (4, 0.8203592896461487), (6, 0.7170542478561401), (8, 0.40613025426864624), (10, 0.7290076613426208), (12, 0.9262295365333557), (14, 0.7458333373069763), (16, 0.875), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 20:57:40,253 | 2092374713.py:37 | Aggregated accuracy: 0.7153939872980117 +- 0.16641650371966674\n",
      "DEBUG flower 2022-04-08 20:57:40,254 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:47,191 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:57:47,211 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:50,378 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:57:50,378 | 2092374713.py:15 | round-143-EVALUATION\n",
      "INFO flower 2022-04-08 20:57:50,381 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8243513107299805), (6, 0.7829457521438599), (8, 0.39080458879470825), (10, 0.7442747950553894), (12, 0.9262295365333557), (14, 0.7250000238418579), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 20:57:50,381 | 2092374713.py:37 | Aggregated accuracy: 0.7160022526979446 +- 0.17588180162614572\n",
      "DEBUG flower 2022-04-08 20:57:50,382 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:57:57,342 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:57:57,364 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:00,179 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:00,179 | 2092374713.py:15 | round-144-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:00,182 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.826347291469574), (6, 0.7984496355056763), (8, 0.37547892332077026), (10, 0.7442747950553894), (12, 0.9303278923034668), (14, 0.7250000238418579), (16, 0.8712121248245239), (18, 0.8795180916786194), (20, 0.5490196347236633)]\n",
      "INFO flower 2022-04-08 20:58:00,182 | 2092374713.py:37 | Aggregated accuracy: 0.7146687239408493 +- 0.18241957811800094\n",
      "DEBUG flower 2022-04-08 20:58:00,183 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:07,445 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:58:07,467 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:10,391 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:10,392 | 2092374713.py:15 | round-145-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:10,394 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8243513107299805), (6, 0.7403100728988647), (8, 0.40229883790016174), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.7416666746139526), (16, 0.875), (18, 0.8755019903182983), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 20:58:10,394 | 2092374713.py:37 | Aggregated accuracy: 0.7172875285148621 +- 0.16883591330535033\n",
      "DEBUG flower 2022-04-08 20:58:10,395 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:17,554 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:58:17,574 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:20,279 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:20,279 | 2092374713.py:15 | round-146-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:20,282 | 2092374713.py:31 | [(2, 0.48627451062202454), (4, 0.8203592896461487), (6, 0.7403100728988647), (8, 0.39463600516319275), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:58:20,282 | 2092374713.py:37 | Aggregated accuracy: 0.7157253086566925 +- 0.16991925740306232\n",
      "DEBUG flower 2022-04-08 20:58:20,283 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:27,403 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:58:27,424 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:30,228 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:30,229 | 2092374713.py:15 | round-147-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:30,231 | 2092374713.py:31 | [(2, 0.48235294222831726), (4, 0.8163672685623169), (6, 0.7364341020584106), (8, 0.40229883790016174), (10, 0.7290076613426208), (12, 0.9262295365333557), (14, 0.7416666746139526), (16, 0.875), (18, 0.8795180916786194), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:58:30,232 | 2092374713.py:37 | Aggregated accuracy: 0.714965945482254 +- 0.1687054587325713\n",
      "DEBUG flower 2022-04-08 20:58:30,233 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:37,179 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:58:37,200 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:39,780 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:39,780 | 2092374713.py:15 | round-148-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:39,783 | 2092374713.py:31 | [(2, 0.48235294222831726), (4, 0.8183632493019104), (6, 0.7558139562606812), (8, 0.39846742153167725), (10, 0.7290076613426208), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:58:39,783 | 2092374713.py:37 | Aggregated accuracy: 0.7163037210702896 +- 0.1698291272698053\n",
      "DEBUG flower 2022-04-08 20:58:39,784 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:46,792 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:58:46,813 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:49,421 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:49,421 | 2092374713.py:15 | round-149-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:49,423 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8203592896461487), (6, 0.7790697813034058), (8, 0.39080458879470825), (10, 0.7442747950553894), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 20:58:49,424 | 2092374713.py:37 | Aggregated accuracy: 0.7172363966703414 +- 0.17536974310571873\n",
      "DEBUG flower 2022-04-08 20:58:49,424 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:56,492 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:58:56,513 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:58:59,357 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:58:59,358 | 2092374713.py:15 | round-150-EVALUATION\n",
      "INFO flower 2022-04-08 20:58:59,361 | 2092374713.py:31 | [(2, 0.48235294222831726), (4, 0.8223552703857422), (6, 0.7403100728988647), (8, 0.40613025426864624), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.7458333373069763), (16, 0.875), (18, 0.8755019903182983), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:58:59,361 | 2092374713.py:37 | Aggregated accuracy: 0.7171138972043991 +- 0.16817447928865045\n",
      "DEBUG flower 2022-04-08 20:58:59,362 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:06,313 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:59:06,334 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:08,968 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:59:08,968 | 2092374713.py:15 | round-151-EVALUATION\n",
      "INFO flower 2022-04-08 20:59:08,970 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.7829457521438599), (8, 0.39080458879470825), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.7333333492279053), (16, 0.875), (18, 0.8755019903182983), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:59:08,971 | 2092374713.py:37 | Aggregated accuracy: 0.7169876307249069 +- 0.1743781113073326\n",
      "DEBUG flower 2022-04-08 20:59:08,971 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:15,925 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:59:15,945 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:18,745 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:59:18,745 | 2092374713.py:15 | round-152-EVALUATION\n",
      "INFO flower 2022-04-08 20:59:18,748 | 2092374713.py:31 | [(2, 0.48235294222831726), (4, 0.8203592896461487), (6, 0.7364341020584106), (8, 0.4214559495449066), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8755019903182983), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:59:18,748 | 2092374713.py:37 | Aggregated accuracy: 0.7172259390354156 +- 0.16508757820034137\n",
      "DEBUG flower 2022-04-08 20:59:18,749 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:25,640 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:59:25,660 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:28,271 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:59:28,271 | 2092374713.py:15 | round-153-EVALUATION\n",
      "INFO flower 2022-04-08 20:59:28,274 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8183632493019104), (6, 0.748062014579773), (8, 0.4214559495449066), (10, 0.732824444770813), (12, 0.9262295365333557), (14, 0.7333333492279053), (16, 0.8787878751754761), (18, 0.8795180916786194), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 20:59:28,274 | 2092374713.py:37 | Aggregated accuracy: 0.7173868656158447 +- 0.16693430146868168\n",
      "DEBUG flower 2022-04-08 20:59:28,275 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:35,193 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:59:35,213 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:38,000 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:59:38,001 | 2092374713.py:15 | round-154-EVALUATION\n",
      "INFO flower 2022-04-08 20:59:38,003 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8183632493019104), (6, 0.7906976938247681), (8, 0.39463600516319275), (10, 0.7404580116271973), (12, 0.9221311211585999), (14, 0.7416666746139526), (16, 0.875), (18, 0.8714859485626221), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 20:59:38,004 | 2092374713.py:37 | Aggregated accuracy: 0.7166203439235688 +- 0.17432940717605397\n",
      "DEBUG flower 2022-04-08 20:59:38,004 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:44,895 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:59:44,917 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:47,579 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:59:47,579 | 2092374713.py:15 | round-155-EVALUATION\n",
      "INFO flower 2022-04-08 20:59:47,581 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8203592896461487), (6, 0.8333333134651184), (8, 0.38697317242622375), (10, 0.7442747950553894), (12, 0.9180327653884888), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 20:59:47,582 | 2092374713.py:37 | Aggregated accuracy: 0.7179344356060028 +- 0.18056208564344284\n",
      "DEBUG flower 2022-04-08 20:59:47,582 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:54,512 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 20:59:54,532 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 20:59:57,293 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 20:59:57,293 | 2092374713.py:15 | round-156-EVALUATION\n",
      "INFO flower 2022-04-08 20:59:57,296 | 2092374713.py:31 | [(2, 0.43921568989753723), (4, 0.826347291469574), (6, 0.817829430103302), (8, 0.37931033968925476), (10, 0.7442747950553894), (12, 0.9180327653884888), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5411764979362488)]\n",
      "INFO flower 2022-04-08 20:59:57,296 | 2092374713.py:37 | Aggregated accuracy: 0.7146234273910522 +- 0.18289570321106402\n",
      "DEBUG flower 2022-04-08 20:59:57,296 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:04,228 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:00:04,249 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:06,865 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:00:06,866 | 2092374713.py:15 | round-157-EVALUATION\n",
      "INFO flower 2022-04-08 21:00:06,869 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8183632493019104), (6, 0.713178277015686), (8, 0.4099617004394531), (10, 0.732824444770813), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5647059082984924)]\n",
      "INFO flower 2022-04-08 21:00:06,870 | 2092374713.py:37 | Aggregated accuracy: 0.7135712593793869 +- 0.16744442093713433\n",
      "DEBUG flower 2022-04-08 21:00:06,870 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:13,960 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:00:13,981 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:16,597 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:00:16,598 | 2092374713.py:15 | round-158-EVALUATION\n",
      "INFO flower 2022-04-08 21:00:16,600 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8203592896461487), (6, 0.7674418687820435), (8, 0.38697317242622375), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.7333333492279053), (16, 0.875), (18, 0.8755019903182983), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 21:00:16,601 | 2092374713.py:37 | Aggregated accuracy: 0.7148545026779175 +- 0.1740429821952747\n",
      "DEBUG flower 2022-04-08 21:00:16,601 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:23,535 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:00:23,556 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:26,204 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:00:26,205 | 2092374713.py:15 | round-159-EVALUATION\n",
      "INFO flower 2022-04-08 21:00:26,207 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8243513107299805), (6, 0.8217054009437561), (8, 0.38314175605773926), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.737500011920929), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 21:00:26,208 | 2092374713.py:37 | Aggregated accuracy: 0.7171975404024125 +- 0.18124960020870648\n",
      "DEBUG flower 2022-04-08 21:00:26,209 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:33,306 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:00:33,327 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:35,921 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:00:35,922 | 2092374713.py:15 | round-160-EVALUATION\n",
      "INFO flower 2022-04-08 21:00:35,924 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8143712282180786), (6, 0.7364341020584106), (8, 0.40229883790016174), (10, 0.7366412281990051), (12, 0.9221311211585999), (14, 0.7458333373069763), (16, 0.875), (18, 0.8795180916786194), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 21:00:35,924 | 2092374713.py:37 | Aggregated accuracy: 0.7147522091865539 +- 0.1693286772202076\n",
      "DEBUG flower 2022-04-08 21:00:35,925 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:42,831 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:00:42,851 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:45,650 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:00:45,651 | 2092374713.py:15 | round-161-EVALUATION\n",
      "INFO flower 2022-04-08 21:00:45,653 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8183632493019104), (6, 0.7596899271011353), (8, 0.39080458879470825), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.7458333373069763), (16, 0.875), (18, 0.8795180916786194), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:00:45,653 | 2092374713.py:37 | Aggregated accuracy: 0.7163066118955612 +- 0.17317287554681743\n",
      "DEBUG flower 2022-04-08 21:00:45,654 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:52,572 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:00:52,593 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:00:55,297 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:00:55,297 | 2092374713.py:15 | round-162-EVALUATION\n",
      "INFO flower 2022-04-08 21:00:55,299 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.826347291469574), (6, 0.8410852551460266), (8, 0.36781609058380127), (10, 0.7480915784835815), (12, 0.9221311211585999), (14, 0.737500011920929), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.529411792755127)]\n",
      "INFO flower 2022-04-08 21:00:55,300 | 2092374713.py:37 | Aggregated accuracy: 0.716971579194069 +- 0.1873093393903322\n",
      "DEBUG flower 2022-04-08 21:00:55,301 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:02,252 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:01:02,272 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:05,095 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:01:05,095 | 2092374713.py:15 | round-163-EVALUATION\n",
      "INFO flower 2022-04-08 21:01:05,098 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8203592896461487), (6, 0.8062015771865845), (8, 0.39080458879470825), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.75), (16, 0.875), (18, 0.8714859485626221), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 21:01:05,099 | 2092374713.py:37 | Aggregated accuracy: 0.7176335781812668 +- 0.17835296488295324\n",
      "DEBUG flower 2022-04-08 21:01:05,099 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:11,993 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:01:12,014 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:14,671 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:01:14,671 | 2092374713.py:15 | round-164-EVALUATION\n",
      "INFO flower 2022-04-08 21:01:14,673 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8223552703857422), (6, 0.7713178396224976), (8, 0.4099617004394531), (10, 0.732824444770813), (12, 0.9262295365333557), (14, 0.7458333373069763), (16, 0.875), (18, 0.8795180916786194), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 21:01:14,674 | 2092374713.py:37 | Aggregated accuracy: 0.7182648092508316 +- 0.17150033520752492\n",
      "DEBUG flower 2022-04-08 21:01:14,674 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:21,571 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:01:21,592 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:24,406 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:01:24,406 | 2092374713.py:15 | round-165-EVALUATION\n",
      "INFO flower 2022-04-08 21:01:24,409 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8203592896461487), (6, 0.751937985420227), (8, 0.4291187822818756), (10, 0.732824444770813), (12, 0.9303278923034668), (14, 0.7458333373069763), (16, 0.875), (18, 0.8795180916786194), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:01:24,409 | 2092374713.py:37 | Aggregated accuracy: 0.7188449263572693 +- 0.16763733666603955\n",
      "DEBUG flower 2022-04-08 21:01:24,409 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:31,315 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:01:31,335 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:33,941 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:01:33,942 | 2092374713.py:15 | round-166-EVALUATION\n",
      "INFO flower 2022-04-08 21:01:33,944 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8223552703857422), (6, 0.7713178396224976), (8, 0.39463600516319275), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.75), (16, 0.875), (18, 0.8795180916786194), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:01:33,945 | 2092374713.py:37 | Aggregated accuracy: 0.7171384274959565 +- 0.17518431488490824\n",
      "DEBUG flower 2022-04-08 21:01:33,945 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:40,875 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:01:40,896 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:43,735 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:01:43,736 | 2092374713.py:15 | round-167-EVALUATION\n",
      "INFO flower 2022-04-08 21:01:43,738 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8183632493019104), (6, 0.817829430103302), (8, 0.38314175605773926), (10, 0.7442747950553894), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5372549295425415)]\n",
      "INFO flower 2022-04-08 21:01:43,740 | 2092374713.py:37 | Aggregated accuracy: 0.7170092195272446 +- 0.1820149507742067\n",
      "DEBUG flower 2022-04-08 21:01:43,740 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:50,658 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:01:50,679 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:01:53,283 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:01:53,284 | 2092374713.py:15 | round-168-EVALUATION\n",
      "INFO flower 2022-04-08 21:01:53,286 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8183632493019104), (6, 0.7364341020584106), (8, 0.4252873659133911), (10, 0.732824444770813), (12, 0.9303278923034668), (14, 0.7416666746139526), (16, 0.875), (18, 0.8795180916786194), (20, 0.5647059082984924)]\n",
      "INFO flower 2022-04-08 21:01:53,287 | 2092374713.py:37 | Aggregated accuracy: 0.7178637534379959 +- 0.16597582814626957\n",
      "DEBUG flower 2022-04-08 21:01:53,287 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:00,215 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:00,236 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:03,032 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:02:03,032 | 2092374713.py:15 | round-169-EVALUATION\n",
      "INFO flower 2022-04-08 21:02:03,034 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8223552703857422), (6, 0.7829457521438599), (8, 0.38697317242622375), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.7458333373069763), (16, 0.875), (18, 0.8755019903182983), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 21:02:03,035 | 2092374713.py:37 | Aggregated accuracy: 0.7167061805725098 +- 0.17658651986175236\n",
      "DEBUG flower 2022-04-08 21:02:03,035 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:09,938 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:09,959 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:12,577 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:02:12,578 | 2092374713.py:15 | round-170-EVALUATION\n",
      "INFO flower 2022-04-08 21:02:12,580 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7403100728988647), (8, 0.4252873659133911), (10, 0.7366412281990051), (12, 0.9303278923034668), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 21:02:12,581 | 2092374713.py:37 | Aggregated accuracy: 0.7184176534414292 +- 0.1665258846092463\n",
      "DEBUG flower 2022-04-08 21:02:12,581 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:19,503 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:19,524 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:22,372 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:02:22,373 | 2092374713.py:15 | round-171-EVALUATION\n",
      "INFO flower 2022-04-08 21:02:22,375 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8163672685623169), (6, 0.7325581312179565), (8, 0.4252873659133911), (10, 0.7290076613426208), (12, 0.9303278923034668), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5843137502670288)]\n",
      "INFO flower 2022-04-08 21:02:22,376 | 2092374713.py:37 | Aggregated accuracy: 0.7188573509454728 +- 0.16470719566950176\n",
      "DEBUG flower 2022-04-08 21:02:22,376 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:29,321 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:29,342 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:31,916 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:02:31,917 | 2092374713.py:15 | round-172-EVALUATION\n",
      "INFO flower 2022-04-08 21:02:31,919 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8163672685623169), (6, 0.7441860437393188), (8, 0.4252873659133911), (10, 0.7366412281990051), (12, 0.9221311211585999), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.572549045085907)]\n",
      "INFO flower 2022-04-08 21:02:31,920 | 2092374713.py:37 | Aggregated accuracy: 0.7179768413305283 +- 0.16478635391114752\n",
      "DEBUG flower 2022-04-08 21:02:31,920 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:39,021 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:39,042 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:41,677 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:02:41,677 | 2092374713.py:15 | round-173-EVALUATION\n",
      "INFO flower 2022-04-08 21:02:41,680 | 2092374713.py:31 | [(2, 0.45098039507865906), (4, 0.8203592896461487), (6, 0.8023256063461304), (8, 0.37931033968925476), (10, 0.7442747950553894), (12, 0.9262295365333557), (14, 0.7458333373069763), (16, 0.875), (18, 0.8755019903182983), (20, 0.545098066329956)]\n",
      "INFO flower 2022-04-08 21:02:41,680 | 2092374713.py:37 | Aggregated accuracy: 0.7164913356304169 +- 0.18103899630225292\n",
      "DEBUG flower 2022-04-08 21:02:41,681 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:48,611 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:48,632 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:51,506 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:02:51,507 | 2092374713.py:15 | round-174-EVALUATION\n",
      "INFO flower 2022-04-08 21:02:51,509 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8203592896461487), (6, 0.7790697813034058), (8, 0.37547892332077026), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.75), (16, 0.875), (18, 0.8795180916786194), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 21:02:51,510 | 2092374713.py:37 | Aggregated accuracy: 0.7161799937486648 +- 0.17875093635772552\n",
      "DEBUG flower 2022-04-08 21:02:51,510 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:02:58,578 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:02:58,600 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:01,256 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:01,257 | 2092374713.py:15 | round-175-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:01,259 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7751938104629517), (8, 0.37931033968925476), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.7416666746139526), (16, 0.875), (18, 0.8795180916786194), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 21:03:01,260 | 2092374713.py:37 | Aggregated accuracy: 0.7165186762809753 +- 0.176105163980684\n",
      "DEBUG flower 2022-04-08 21:03:01,261 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:08,211 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:03:08,231 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:11,055 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:11,055 | 2092374713.py:15 | round-176-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:11,058 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7441860437393188), (8, 0.4291187822818756), (10, 0.7290076613426208), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 21:03:11,058 | 2092374713.py:37 | Aggregated accuracy: 0.7191899836063385 +- 0.1638650131653696\n",
      "DEBUG flower 2022-04-08 21:03:11,059 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:17,984 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:03:18,005 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:20,652 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:20,653 | 2092374713.py:15 | round-177-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:20,656 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7635658979415894), (8, 0.39080458879470825), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 21:03:20,656 | 2092374713.py:37 | Aggregated accuracy: 0.7172755926847458 +- 0.1720550115312404\n",
      "DEBUG flower 2022-04-08 21:03:20,656 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:27,576 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:03:27,597 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:30,424 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:30,425 | 2092374713.py:15 | round-178-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:30,427 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8243513107299805), (6, 0.786821722984314), (8, 0.37547892332077026), (10, 0.7404580116271973), (12, 0.9221311211585999), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5490196347236633)]\n",
      "INFO flower 2022-04-08 21:03:30,427 | 2092374713.py:37 | Aggregated accuracy: 0.7160883933305741 +- 0.17845099883966856\n",
      "DEBUG flower 2022-04-08 21:03:30,428 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:37,344 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:03:37,365 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:39,969 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:39,970 | 2092374713.py:15 | round-179-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:39,972 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7635658979415894), (8, 0.4176245331764221), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.7291666865348816), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 21:03:39,973 | 2092374713.py:37 | Aggregated accuracy: 0.7199211031198501 +- 0.1680220058162551\n",
      "DEBUG flower 2022-04-08 21:03:39,973 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:46,957 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:03:46,979 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:49,797 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:49,797 | 2092374713.py:15 | round-180-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:49,799 | 2092374713.py:31 | [(2, 0.48627451062202454), (4, 0.8163672685623169), (6, 0.7325581312179565), (8, 0.39080458879470825), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.7333333492279053), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 21:03:49,800 | 2092374713.py:37 | Aggregated accuracy: 0.7160884231328964 +- 0.1694455221392337\n",
      "DEBUG flower 2022-04-08 21:03:49,801 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:56,696 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:03:56,717 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:03:59,330 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:03:59,331 | 2092374713.py:15 | round-181-EVALUATION\n",
      "INFO flower 2022-04-08 21:03:59,334 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7829457521438599), (8, 0.37547892332077026), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.7416666746139526), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 21:03:59,334 | 2092374713.py:37 | Aggregated accuracy: 0.7176494032144547 +- 0.17637635895454026\n",
      "DEBUG flower 2022-04-08 21:03:59,334 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:06,296 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:04:06,317 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:08,945 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:04:08,945 | 2092374713.py:15 | round-182-EVALUATION\n",
      "INFO flower 2022-04-08 21:04:08,947 | 2092374713.py:31 | [(2, 0.4901960790157318), (4, 0.8163672685623169), (6, 0.713178277015686), (8, 0.4214559495449066), (10, 0.732824444770813), (12, 0.9262295365333557), (14, 0.7291666865348816), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 21:04:08,948 | 2092374713.py:37 | Aggregated accuracy: 0.7156524538993836 +- 0.1613685228844232\n",
      "DEBUG flower 2022-04-08 21:04:08,948 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:16,051 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:04:16,072 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:18,706 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:04:18,706 | 2092374713.py:15 | round-183-EVALUATION\n",
      "INFO flower 2022-04-08 21:04:18,709 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8183632493019104), (6, 0.7248061895370483), (8, 0.4214559495449066), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5803921818733215)]\n",
      "INFO flower 2022-04-08 21:04:18,710 | 2092374713.py:37 | Aggregated accuracy: 0.7170183956623077 +- 0.1633268895759432\n",
      "DEBUG flower 2022-04-08 21:04:18,711 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:25,656 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:04:25,677 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:28,477 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:04:28,477 | 2092374713.py:15 | round-184-EVALUATION\n",
      "INFO flower 2022-04-08 21:04:28,480 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8203592896461487), (6, 0.7558139562606812), (8, 0.4252873659133911), (10, 0.7290076613426208), (12, 0.9303278923034668), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 21:04:28,480 | 2092374713.py:37 | Aggregated accuracy: 0.719574561715126 +- 0.16392289445614783\n",
      "DEBUG flower 2022-04-08 21:04:28,481 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:35,414 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:04:35,434 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:38,110 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:04:38,111 | 2092374713.py:15 | round-185-EVALUATION\n",
      "INFO flower 2022-04-08 21:04:38,113 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8183632493019104), (6, 0.7596899271011353), (8, 0.4176245331764221), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 21:04:38,114 | 2092374713.py:37 | Aggregated accuracy: 0.719349792599678 +- 0.16482254287939035\n",
      "DEBUG flower 2022-04-08 21:04:38,114 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:45,066 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:04:45,088 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:47,722 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:04:47,723 | 2092374713.py:15 | round-186-EVALUATION\n",
      "INFO flower 2022-04-08 21:04:47,726 | 2092374713.py:31 | [(2, 0.47843137383461), (4, 0.8203592896461487), (6, 0.7674418687820435), (8, 0.4214559495449066), (10, 0.7366412281990051), (12, 0.9262295365333557), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 21:04:47,726 | 2092374713.py:37 | Aggregated accuracy: 0.7199234187602996 +- 0.16515191715821956\n",
      "DEBUG flower 2022-04-08 21:04:47,727 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:55,616 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:04:55,637 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:04:58,270 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:04:58,271 | 2092374713.py:15 | round-187-EVALUATION\n",
      "INFO flower 2022-04-08 21:04:58,273 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8183632493019104), (6, 0.8062015771865845), (8, 0.38314175605773926), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8755019903182983), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:04:58,273 | 2092374713.py:37 | Aggregated accuracy: 0.7174160867929459 +- 0.17856784336449597\n",
      "DEBUG flower 2022-04-08 21:04:58,274 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:05,286 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:05:05,307 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:08,099 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:05:08,100 | 2092374713.py:15 | round-188-EVALUATION\n",
      "INFO flower 2022-04-08 21:05:08,102 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8223552703857422), (6, 0.817829430103302), (8, 0.37931033968925476), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.7458333373069763), (16, 0.8901515007019043), (18, 0.8714859485626221), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 21:05:08,103 | 2092374713.py:37 | Aggregated accuracy: 0.7205136477947235 +- 0.18062362445986868\n",
      "DEBUG flower 2022-04-08 21:05:08,103 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:15,154 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:05:15,175 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:17,653 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:05:17,654 | 2092374713.py:15 | round-189-EVALUATION\n",
      "INFO flower 2022-04-08 21:05:17,656 | 2092374713.py:31 | [(2, 0.4588235318660736), (4, 0.8183632493019104), (6, 0.7984496355056763), (8, 0.40229883790016174), (10, 0.7442747950553894), (12, 0.9303278923034668), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:05:17,657 | 2092374713.py:37 | Aggregated accuracy: 0.720550787448883 +- 0.1747122213436962\n",
      "DEBUG flower 2022-04-08 21:05:17,658 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:24,595 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:05:24,617 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:27,265 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:05:27,265 | 2092374713.py:15 | round-190-EVALUATION\n",
      "INFO flower 2022-04-08 21:05:27,267 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8203592896461487), (6, 0.7790697813034058), (8, 0.40613025426864624), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:05:27,268 | 2092374713.py:37 | Aggregated accuracy: 0.718781128525734 +- 0.17253042650868525\n",
      "DEBUG flower 2022-04-08 21:05:27,268 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:34,492 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:05:34,513 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:37,111 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:05:37,112 | 2092374713.py:15 | round-191-EVALUATION\n",
      "INFO flower 2022-04-08 21:05:37,114 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.7829457521438599), (8, 0.39846742153167725), (10, 0.7404580116271973), (12, 0.9221311211585999), (14, 0.7416666746139526), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5529412031173706)]\n",
      "INFO flower 2022-04-08 21:05:37,114 | 2092374713.py:37 | Aggregated accuracy: 0.7177772253751755 +- 0.1740646771388634\n",
      "DEBUG flower 2022-04-08 21:05:37,115 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:44,079 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:05:44,099 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:46,705 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:05:46,705 | 2092374713.py:15 | round-192-EVALUATION\n",
      "INFO flower 2022-04-08 21:05:46,709 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8223552703857422), (6, 0.7635658979415894), (8, 0.4176245331764221), (10, 0.7404580116271973), (12, 0.9262295365333557), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5686274766921997)]\n",
      "INFO flower 2022-04-08 21:05:46,709 | 2092374713.py:37 | Aggregated accuracy: 0.7193623930215836 +- 0.16900343031158443\n",
      "DEBUG flower 2022-04-08 21:05:46,710 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:53,866 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:05:53,887 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:05:56,478 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:05:56,479 | 2092374713.py:15 | round-193-EVALUATION\n",
      "INFO flower 2022-04-08 21:05:56,481 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8223552703857422), (6, 0.7635658979415894), (8, 0.4176245331764221), (10, 0.732824444770813), (12, 0.9303278923034668), (14, 0.737500011920929), (16, 0.875), (18, 0.8795180916786194), (20, 0.5764706134796143)]\n",
      "INFO flower 2022-04-08 21:05:56,482 | 2092374713.py:37 | Aggregated accuracy: 0.7209696561098099 +- 0.1669855654002346\n",
      "DEBUG flower 2022-04-08 21:05:56,482 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:03,469 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:06:03,490 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:06,085 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:06:06,085 | 2092374713.py:15 | round-194-EVALUATION\n",
      "INFO flower 2022-04-08 21:06:06,087 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8203592896461487), (6, 0.7945736646652222), (8, 0.4137931168079376), (10, 0.7404580116271973), (12, 0.9303278923034668), (14, 0.7458333373069763), (16, 0.875), (18, 0.8755019903182983), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 21:06:06,088 | 2092374713.py:37 | Aggregated accuracy: 0.7219376742839814 +- 0.1715860194385313\n",
      "DEBUG flower 2022-04-08 21:06:06,089 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:13,236 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:06:13,257 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:15,851 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:06:15,852 | 2092374713.py:15 | round-195-EVALUATION\n",
      "INFO flower 2022-04-08 21:06:15,854 | 2092374713.py:31 | [(2, 0.46666666865348816), (4, 0.8223552703857422), (6, 0.7674418687820435), (8, 0.4099617004394531), (10, 0.7366412281990051), (12, 0.9221311211585999), (14, 0.7416666746139526), (16, 0.8787878751754761), (18, 0.8755019903182983), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 21:06:15,855 | 2092374713.py:37 | Aggregated accuracy: 0.7181938737630844 +- 0.1701010539226115\n",
      "DEBUG flower 2022-04-08 21:06:15,855 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:22,789 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:06:22,810 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:25,432 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:06:25,432 | 2092374713.py:15 | round-196-EVALUATION\n",
      "INFO flower 2022-04-08 21:06:25,435 | 2092374713.py:31 | [(2, 0.4470588266849518), (4, 0.8203592896461487), (6, 0.7945736646652222), (8, 0.39080458879470825), (10, 0.7442747950553894), (12, 0.9221311211585999), (14, 0.7458333373069763), (16, 0.8787878751754761), (18, 0.8714859485626221), (20, 0.5568627715110779)]\n",
      "INFO flower 2022-04-08 21:06:25,435 | 2092374713.py:37 | Aggregated accuracy: 0.7172172218561172 +- 0.1775700529799585\n",
      "DEBUG flower 2022-04-08 21:06:25,436 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:32,602 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:06:32,625 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:35,230 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:06:35,230 | 2092374713.py:15 | round-197-EVALUATION\n",
      "INFO flower 2022-04-08 21:06:35,233 | 2092374713.py:31 | [(2, 0.45490196347236633), (4, 0.8183632493019104), (6, 0.7945736646652222), (8, 0.40613025426864624), (10, 0.7366412281990051), (12, 0.9221311211585999), (14, 0.7416666746139526), (16, 0.8825757503509521), (18, 0.8714859485626221), (20, 0.5607843399047852)]\n",
      "INFO flower 2022-04-08 21:06:35,233 | 2092374713.py:37 | Aggregated accuracy: 0.7189254194498063 +- 0.1733055274181386\n",
      "DEBUG flower 2022-04-08 21:06:35,234 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:42,220 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:06:42,241 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:44,856 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:06:44,857 | 2092374713.py:15 | round-198-EVALUATION\n",
      "INFO flower 2022-04-08 21:06:44,859 | 2092374713.py:31 | [(2, 0.4745098054409027), (4, 0.8203592896461487), (6, 0.7403100728988647), (8, 0.4252873659133911), (10, 0.7251908183097839), (12, 0.9467213153839111), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.6039215922355652)]\n",
      "INFO flower 2022-04-08 21:06:44,860 | 2092374713.py:37 | Aggregated accuracy: 0.7216347724199295 +- 0.1642273374525427\n",
      "DEBUG flower 2022-04-08 21:06:44,860 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:52,062 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:06:52,084 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:06:54,756 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:06:54,756 | 2092374713.py:15 | round-199-EVALUATION\n",
      "INFO flower 2022-04-08 21:06:54,759 | 2092374713.py:31 | [(2, 0.47058823704719543), (4, 0.8223552703857422), (6, 0.7635658979415894), (8, 0.4291187822818756), (10, 0.7251908183097839), (12, 0.9426229596138), (14, 0.7333333492279053), (16, 0.8712121248245239), (18, 0.8755019903182983), (20, 0.6039215922355652)]\n",
      "INFO flower 2022-04-08 21:06:54,759 | 2092374713.py:37 | Aggregated accuracy: 0.723741102218628 +- 0.16411539174650563\n",
      "DEBUG flower 2022-04-08 21:06:54,760 | server.py:265 | fit_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:07:01,831 | server.py:277 | fit_round received 10 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:07:01,852 | server.py:211 | evaluate_round: strategy sampled 10 clients (out of 10)\n",
      "DEBUG flower 2022-04-08 21:07:04,444 | server.py:223 | evaluate_round received 10 results and 0 failures\n",
      "INFO flower 2022-04-08 21:07:04,445 | 2092374713.py:15 | round-200-EVALUATION\n",
      "INFO flower 2022-04-08 21:07:04,447 | 2092374713.py:31 | [(2, 0.4627451002597809), (4, 0.8163672685623169), (6, 0.7635658979415894), (8, 0.4214559495449066), (10, 0.7366412281990051), (12, 0.9344262480735779), (14, 0.7291666865348816), (16, 0.8674242496490479), (18, 0.8755019903182983), (20, 0.6000000238418579)]\n",
      "INFO flower 2022-04-08 21:07:04,448 | 2092374713.py:37 | Aggregated accuracy: 0.7207294642925263 +- 0.16527017195215984\n",
      "INFO flower 2022-04-08 21:07:04,448 | server.py:182 | FL finished in 1885.1399757\n",
      "INFO flower 2022-04-08 21:07:04,449 | app.py:149 | app_fit: losses_distributed [(1, 0.7133335119167422), (2, 0.6876333056277552), (3, 0.6649732467050234), (4, 0.6453647801593112), (5, 0.6301129521243074), (6, 0.6173851186761552), (7, 0.6066766574888001), (8, 0.5972515049481657), (9, 0.589440986562177), (10, 0.583279550267873), (11, 0.5784293606572786), (12, 0.5747904411542796), (13, 0.5715773763217221), (14, 0.5688915165063086), (15, 0.568634952245198), (16, 0.5683305586974396), (17, 0.5683884195376998), (18, 0.5687240124518147), (19, 0.5696468814144258), (20, 0.5687998266000396), (21, 0.5697224274806627), (22, 0.5719391778512171), (23, 0.5730197972061387), (24, 0.5741346303324154), (25, 0.5746167464446919), (26, 0.5732120128462673), (27, 0.5736339216849504), (28, 0.574389526026785), (29, 0.5747866694668196), (30, 0.575220127661795), (31, 0.576758146788237), (32, 0.5758478502810066), (33, 0.575409976501711), (34, 0.5759048695502721), (35, 0.5745496347135179), (36, 0.5747720531106807), (37, 0.5744284100646228), (38, 0.5739489914204922), (39, 0.5746686542042698), (40, 0.5729313712472256), (41, 0.5736217874166742), (42, 0.5721869884254515), (43, 0.5733805992732385), (44, 0.5720497077940698), (45, 0.5724317963489198), (46, 0.5736944740307549), (47, 0.5752487267888802), (48, 0.5744225975966188), (49, 0.5734005132406234), (50, 0.5738913790647083), (51, 0.5727011512987671), (52, 0.5716657145192607), (53, 0.5680167680468), (54, 0.569791388740331), (55, 0.5675424514555427), (56, 0.5686810650398929), (57, 0.5676754307644305), (58, 0.5667901352961545), (59, 0.5664262472942081), (60, 0.5678801861297448), (61, 0.5704821993604532), (62, 0.5686883914103086), (63, 0.5654550340065353), (64, 0.5642295030014794), (65, 0.5653823747050168), (66, 0.5652396207152408), (67, 0.5655006261528415), (68, 0.5670371025362593), (69, 0.5653837206287596), (70, 0.5640008097034322), (71, 0.5661133198530369), (72, 0.5653978619215607), (73, 0.5637320852506199), (74, 0.5648204732449861), (75, 0.5642104682186334), (76, 0.5626717347767927), (77, 0.5653208040366168), (78, 0.5657762298984911), (79, 0.5665925776137807), (80, 0.566134537760183), (81, 0.5672836482375273), (82, 0.5675161583592876), (83, 0.5656082197708568), (84, 0.5681954037228465), (85, 0.5669729369607353), (86, 0.5678447709582791), (87, 0.568354442966758), (88, 0.5654471918176519), (89, 0.565490136312387), (90, 0.5651509645336543), (91, 0.5679377461257653), (92, 0.5654954834730662), (93, 0.5653904059660738), (94, 0.5649084482581097), (95, 0.5637588574814514), (96, 0.562715210904781), (97, 0.5646662970049144), (98, 0.564023805790881), (99, 0.5639832470099873), (100, 0.5637035628145594), (101, 0.5645388571559506), (102, 0.566088850276365), (103, 0.563733264114661), (104, 0.5632159041755727), (105, 0.5674401951887651), (106, 0.5668588029350932), (107, 0.5650231831387492), (108, 0.5623562774507749), (109, 0.5624988160282106), (110, 0.5607081540556696), (111, 0.56025751810768), (112, 0.5622578726720109), (113, 0.563614830016748), (114, 0.5647069833192316), (115, 0.5637434150271623), (116, 0.5623984874448882), (117, 0.5629463877759984), (118, 0.5632549197325872), (119, 0.5617556376733331), (120, 0.5624290432883831), (121, 0.5629554869518266), (122, 0.5596097056243359), (123, 0.5605326633314028), (124, 0.5598542398344706), (125, 0.5577458323287725), (126, 0.5588051838638023), (127, 0.5615648974672189), (128, 0.5592070410182375), (129, 0.5594440026708981), (130, 0.5625684883548351), (131, 0.5644319974401596), (132, 0.5621234266379265), (133, 0.5616437819919606), (134, 0.5643139786833972), (135, 0.5607972581483165), (136, 0.5618005583003329), (137, 0.5620511707844124), (138, 0.5619040237677572), (139, 0.5630157731711202), (140, 0.5608001232425044), (141, 0.5585486674744752), (142, 0.5586211731054314), (143, 0.561161230022055), (144, 0.5624635985415655), (145, 0.5596656349449869), (146, 0.5589886379417188), (147, 0.5582275970856662), (148, 0.5587568186696348), (149, 0.5610629714125157), (150, 0.5580166427304386), (151, 0.5603929273904374), (152, 0.5578681478131925), (153, 0.5585683567223048), (154, 0.560267769604355), (155, 0.5630499107109342), (156, 0.5628998803276022), (157, 0.558208820660852), (158, 0.5603027408611992), (159, 0.5634030056239114), (160, 0.5586683041692934), (161, 0.560099347950353), (162, 0.564295851305934), (163, 0.5613072065522312), (164, 0.5589568023614963), (165, 0.5588370041528369), (166, 0.5596136803715064), (167, 0.562254287481479), (168, 0.5577167023378019), (169, 0.5601371695872231), (170, 0.5587732411490927), (171, 0.5568880373835777), (172, 0.5569350057474898), (173, 0.5604336752328192), (174, 0.5595724094016614), (175, 0.5587246661098169), (176, 0.557367568098973), (177, 0.5581458018923712), (178, 0.5599227301661538), (179, 0.5578973068478031), (180, 0.5565976507029425), (181, 0.5584545063583515), (182, 0.5549297804428968), (183, 0.5557029526286674), (184, 0.5560882146553396), (185, 0.5560953039535702), (186, 0.556349632196334), (187, 0.5598782009337272), (188, 0.5610563022212428), (189, 0.5607089770336056), (190, 0.5595832481397955), (191, 0.559858496448138), (192, 0.5579469103610571), (193, 0.5564281678554532), (194, 0.5588417216285919), (195, 0.5564543126026077), (196, 0.5585181487102413), (197, 0.5578291101261637), (198, 0.5539452011929742), (199, 0.5542575188352455), (200, 0.5551718205972229)]\n",
      "INFO flower 2022-04-08 21:07:04,449 | app.py:150 | app_fit: metrics_distributed {}\n",
      "INFO flower 2022-04-08 21:07:04,450 | app.py:151 | app_fit: losses_centralized []\n",
      "INFO flower 2022-04-08 21:07:04,450 | app.py:152 | app_fit: metrics_centralized {}\n",
      "INFO flower 2022-04-08 21:07:09,849 | app.py:144 | Ray initialized with resources: {'CPU': 8.0, 'object_store_memory': 5781759590.0, 'GPU': 1.0, 'memory': 11563519182.0, 'node:127.0.0.1': 1.0}\n",
      "INFO flower 2022-04-08 21:07:09,849 | app.py:153 | Starting Flower simulation running: {'num_rounds': 200}\n",
      "INFO flower 2022-04-08 21:07:09,850 | server.py:128 | Initializing global parameters\n",
      "INFO flower 2022-04-08 21:07:09,850 | server.py:327 | Requesting initial parameters from one random client\n",
      "INFO flower 2022-04-08 21:07:13,725 | server.py:330 | Received initial parameters from one random client\n",
      "INFO flower 2022-04-08 21:07:13,725 | server.py:130 | Evaluating initial parameters\n",
      "INFO flower 2022-04-08 21:07:13,726 | server.py:143 | FL starting\n",
      "DEBUG flower 2022-04-08 21:07:13,726 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:21,527 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:07:21,550 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:24,487 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:07:24,488 | 2092374713.py:15 | round-1-EVALUATION\n",
      "INFO flower 2022-04-08 21:07:24,490 | 2092374713.py:31 | [(1, 0.747035562992096), (3, 0.5785440802574158), (5, 0.4790419042110443), (7, 0.6521739363670349), (9, 0.30364373326301575), (11, 0.6102362275123596), (13, 0.4752066135406494), (15, 0.3513513505458832), (17, 0.3333333432674408), (19, 0.7007575631141663), (21, 0.2109704613685608)]\n",
      "INFO flower 2022-04-08 21:07:24,491 | 2092374713.py:37 | Aggregated accuracy: 0.49475407058542425 +- 0.16936447068656416\n",
      "DEBUG flower 2022-04-08 21:07:24,491 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:32,082 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:07:32,106 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:35,022 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:07:35,022 | 2092374713.py:15 | round-2-EVALUATION\n",
      "INFO flower 2022-04-08 21:07:35,025 | 2092374713.py:31 | [(1, 0.9090909361839294), (3, 0.6015325784683228), (5, 0.5708582997322083), (7, 0.6640316247940063), (9, 0.3238866329193115), (11, 0.7283464670181274), (13, 0.6280992031097412), (15, 0.4555984437465668), (17, 0.3174603283405304), (19, 0.8409090638160706), (21, 0.3291139304637909)]\n",
      "INFO flower 2022-04-08 21:07:35,025 | 2092374713.py:37 | Aggregated accuracy: 0.578993409872055 +- 0.19568822273259948\n",
      "DEBUG flower 2022-04-08 21:07:35,026 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:42,654 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:07:42,677 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:45,570 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:07:45,571 | 2092374713.py:15 | round-3-EVALUATION\n",
      "INFO flower 2022-04-08 21:07:45,573 | 2092374713.py:31 | [(1, 0.9051383137702942), (3, 0.6015325784683228), (5, 0.6027944087982178), (7, 0.6837944388389587), (9, 0.36032387614250183), (11, 0.7952755689620972), (13, 0.6157024502754211), (15, 0.4710424840450287), (17, 0.289682537317276), (19, 0.8560606241226196), (21, 0.3628692030906677)]\n",
      "INFO flower 2022-04-08 21:07:45,573 | 2092374713.py:37 | Aggregated accuracy: 0.5949287712574005 +- 0.19780774661252384\n",
      "DEBUG flower 2022-04-08 21:07:45,574 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:53,201 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:07:53,224 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:07:56,107 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:07:56,107 | 2092374713.py:15 | round-4-EVALUATION\n",
      "INFO flower 2022-04-08 21:07:56,110 | 2092374713.py:31 | [(1, 0.8498023748397827), (3, 0.6015325784683228), (5, 0.6047903895378113), (7, 0.695652186870575), (9, 0.41295546293258667), (11, 0.8031495809555054), (13, 0.6074380278587341), (15, 0.48262548446655273), (17, 0.3095238208770752), (19, 0.8446969985961914), (21, 0.38818565011024475)]\n",
      "INFO flower 2022-04-08 21:07:56,111 | 2092374713.py:37 | Aggregated accuracy: 0.6000320505012166 +- 0.1785756054502559\n",
      "DEBUG flower 2022-04-08 21:07:56,111 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:03,744 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:08:03,767 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:06,679 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:08:06,679 | 2092374713.py:15 | round-5-EVALUATION\n",
      "INFO flower 2022-04-08 21:08:06,682 | 2092374713.py:31 | [(1, 0.7549406886100769), (3, 0.6015325784683228), (5, 0.652694582939148), (7, 0.695652186870575), (9, 0.4615384638309479), (11, 0.7992125749588013), (13, 0.6363636255264282), (15, 0.5250965356826782), (17, 0.3650793731212616), (19, 0.8257575631141663), (21, 0.4219409227371216)]\n",
      "INFO flower 2022-04-08 21:08:06,682 | 2092374713.py:37 | Aggregated accuracy: 0.6127099178054116 +- 0.14703350455265235\n",
      "DEBUG flower 2022-04-08 21:08:06,683 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:14,268 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:08:14,291 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:17,226 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:08:17,227 | 2092374713.py:15 | round-6-EVALUATION\n",
      "INFO flower 2022-04-08 21:08:17,229 | 2092374713.py:31 | [(1, 0.7272727489471436), (3, 0.5900382995605469), (5, 0.6666666865348816), (7, 0.687747061252594), (9, 0.49392712116241455), (11, 0.7677165269851685), (13, 0.6487603187561035), (15, 0.5444015264511108), (17, 0.408730149269104), (19, 0.7954545617103577), (21, 0.4556961953639984)]\n",
      "INFO flower 2022-04-08 21:08:17,230 | 2092374713.py:37 | Aggregated accuracy: 0.6169464723630385 +- 0.12274950371705154\n",
      "DEBUG flower 2022-04-08 21:08:17,230 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:24,735 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:08:24,759 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:27,716 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:08:27,717 | 2092374713.py:15 | round-7-EVALUATION\n",
      "INFO flower 2022-04-08 21:08:27,719 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.5977011322975159), (5, 0.6726546883583069), (7, 0.6521739363670349), (9, 0.49392712116241455), (11, 0.7795275449752808), (13, 0.6570248007774353), (15, 0.5714285969734192), (17, 0.4563491940498352), (19, 0.7689393758773804), (21, 0.4767932593822479)]\n",
      "INFO flower 2022-04-08 21:08:27,719 | 2092374713.py:37 | Aggregated accuracy: 0.6184008148583499 +- 0.10529030080442707\n",
      "DEBUG flower 2022-04-08 21:08:27,720 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:35,257 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:08:35,280 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:38,430 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:08:38,431 | 2092374713.py:15 | round-8-EVALUATION\n",
      "INFO flower 2022-04-08 21:08:38,433 | 2092374713.py:31 | [(1, 0.6442687511444092), (3, 0.5977011322975159), (5, 0.688622772693634), (7, 0.6403161883354187), (9, 0.5263158082962036), (11, 0.7598425149917603), (13, 0.6694214940071106), (15, 0.6293436288833618), (17, 0.5), (19, 0.7462121248245239), (21, 0.49789029359817505)]\n",
      "INFO flower 2022-04-08 21:08:38,434 | 2092374713.py:37 | Aggregated accuracy: 0.6272667917338285 +- 0.08619739525473631\n",
      "DEBUG flower 2022-04-08 21:08:38,434 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:45,801 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:08:45,825 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:48,620 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:08:48,620 | 2092374713.py:15 | round-9-EVALUATION\n",
      "INFO flower 2022-04-08 21:08:48,622 | 2092374713.py:31 | [(1, 0.6442687511444092), (3, 0.5977011322975159), (5, 0.6906187534332275), (7, 0.6403161883354187), (9, 0.5303643941879272), (11, 0.7401574850082397), (13, 0.6735537052154541), (15, 0.6293436288833618), (17, 0.5158730149269104), (19, 0.7424242496490479), (21, 0.5443037748336792)]\n",
      "INFO flower 2022-04-08 21:08:48,623 | 2092374713.py:37 | Aggregated accuracy: 0.6317204616286538 +- 0.07505308206498051\n",
      "DEBUG flower 2022-04-08 21:08:48,624 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:55,618 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:08:55,641 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:08:58,395 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:08:58,396 | 2092374713.py:15 | round-10-EVALUATION\n",
      "INFO flower 2022-04-08 21:08:58,399 | 2092374713.py:31 | [(1, 0.6482213735580444), (3, 0.6130267977714539), (5, 0.6966068148612976), (7, 0.6324110627174377), (9, 0.5506072640419006), (11, 0.7283464670181274), (13, 0.6776859760284424), (15, 0.6525096297264099), (17, 0.5555555820465088), (19, 0.7234848737716675), (21, 0.5864979028701782)]\n",
      "INFO flower 2022-04-08 21:08:58,399 | 2092374713.py:37 | Aggregated accuracy: 0.6422685222192244 +- 0.05903496754778199\n",
      "DEBUG flower 2022-04-08 21:08:58,399 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:05,714 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:09:05,737 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:08,681 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:09:08,681 | 2092374713.py:15 | round-11-EVALUATION\n",
      "INFO flower 2022-04-08 21:09:08,684 | 2092374713.py:31 | [(1, 0.6521739363670349), (3, 0.6168582439422607), (5, 0.6966068148612976), (7, 0.6126482486724854), (9, 0.5829959511756897), (11, 0.712598443031311), (13, 0.6900826692581177), (15, 0.6795367002487183), (17, 0.5714285969734192), (19, 0.7045454382896423), (21, 0.6160337328910828)]\n",
      "INFO flower 2022-04-08 21:09:08,684 | 2092374713.py:37 | Aggregated accuracy: 0.6486826159737327 +- 0.04846824844781384\n",
      "DEBUG flower 2022-04-08 21:09:08,685 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:16,395 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:09:16,419 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:19,345 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:09:19,345 | 2092374713.py:15 | round-12-EVALUATION\n",
      "INFO flower 2022-04-08 21:09:19,348 | 2092374713.py:31 | [(1, 0.6482213735580444), (3, 0.6168582439422607), (5, 0.6926147937774658), (7, 0.5849802494049072), (9, 0.591093122959137), (11, 0.6968504190444946), (13, 0.6983470916748047), (15, 0.7027027010917664), (17, 0.591269850730896), (19, 0.6931818127632141), (21, 0.6751055121421814)]\n",
      "INFO flower 2022-04-08 21:09:19,348 | 2092374713.py:37 | Aggregated accuracy: 0.6537477428262884 +- 0.046431582916338164\n",
      "DEBUG flower 2022-04-08 21:09:19,349 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:26,979 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:09:27,003 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:29,865 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:09:29,865 | 2092374713.py:15 | round-13-EVALUATION\n",
      "INFO flower 2022-04-08 21:09:29,868 | 2092374713.py:31 | [(1, 0.6403161883354187), (3, 0.6245210766792297), (5, 0.6866267323493958), (7, 0.5810276865959167), (9, 0.5870445370674133), (11, 0.6968504190444946), (13, 0.702479362487793), (15, 0.7142857313156128), (17, 0.60317462682724), (19, 0.6969696879386902), (21, 0.6835442781448364)]\n",
      "INFO flower 2022-04-08 21:09:29,868 | 2092374713.py:37 | Aggregated accuracy: 0.6560763933441855 +- 0.047677493960352486\n",
      "DEBUG flower 2022-04-08 21:09:29,869 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:37,548 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:09:37,571 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:40,450 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:09:40,450 | 2092374713.py:15 | round-14-EVALUATION\n",
      "INFO flower 2022-04-08 21:09:40,452 | 2092374713.py:31 | [(1, 0.6403161883354187), (3, 0.6245210766792297), (5, 0.6926147937774658), (7, 0.5652173757553101), (9, 0.5991902947425842), (11, 0.6968504190444946), (13, 0.7066115736961365), (15, 0.7297297120094299), (17, 0.6071428656578064), (19, 0.7045454382896423), (21, 0.7046413421630859)]\n",
      "INFO flower 2022-04-08 21:09:40,453 | 2092374713.py:37 | Aggregated accuracy: 0.6610346436500549 +- 0.05269428901365421\n",
      "DEBUG flower 2022-04-08 21:09:40,454 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:48,076 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:09:48,099 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:50,990 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:09:50,991 | 2092374713.py:15 | round-15-EVALUATION\n",
      "INFO flower 2022-04-08 21:09:50,993 | 2092374713.py:31 | [(1, 0.6284584999084473), (3, 0.6321839094161987), (5, 0.7025948166847229), (7, 0.5375494360923767), (9, 0.6194332242012024), (11, 0.6732283234596252), (13, 0.6983470916748047), (15, 0.7413127422332764), (17, 0.6428571343421936), (19, 0.7045454382896423), (21, 0.7172995805740356)]\n",
      "INFO flower 2022-04-08 21:09:50,994 | 2092374713.py:37 | Aggregated accuracy: 0.6634372906251387 +- 0.05552347961722242\n",
      "DEBUG flower 2022-04-08 21:09:50,994 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:09:58,597 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:09:58,620 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:01,522 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:10:01,523 | 2092374713.py:15 | round-16-EVALUATION\n",
      "INFO flower 2022-04-08 21:10:01,525 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6245210766792297), (5, 0.7025948166847229), (7, 0.5335968136787415), (9, 0.6194332242012024), (11, 0.6732283234596252), (13, 0.702479362487793), (15, 0.7490347623825073), (17, 0.64682537317276), (19, 0.7121211886405945), (21, 0.7299578189849854)]\n",
      "INFO flower 2022-04-08 21:10:01,525 | 2092374713.py:37 | Aggregated accuracy: 0.6638625806028192 +- 0.06094370307700624\n",
      "DEBUG flower 2022-04-08 21:10:01,526 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:09,090 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:10:09,114 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:12,066 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:10:12,067 | 2092374713.py:15 | round-17-EVALUATION\n",
      "INFO flower 2022-04-08 21:10:12,069 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6321839094161987), (5, 0.7065868377685547), (7, 0.5335968136787415), (9, 0.6113360524177551), (11, 0.6732283234596252), (13, 0.702479362487793), (15, 0.7451737523078918), (17, 0.6507936716079712), (19, 0.7121211886405945), (21, 0.7299578189849854)]\n",
      "INFO flower 2022-04-08 21:10:12,070 | 2092374713.py:37 | Aggregated accuracy: 0.6641957597299055 +- 0.06079625295666431\n",
      "DEBUG flower 2022-04-08 21:10:12,070 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:19,627 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:10:19,651 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:22,572 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:10:22,572 | 2092374713.py:15 | round-18-EVALUATION\n",
      "INFO flower 2022-04-08 21:10:22,574 | 2092374713.py:31 | [(1, 0.6007905006408691), (3, 0.6398467421531677), (5, 0.7105788588523865), (7, 0.5375494360923767), (9, 0.6315789222717285), (11, 0.6692913174629211), (13, 0.6983470916748047), (15, 0.7490347623825073), (17, 0.6666666865348816), (19, 0.7159090638160706), (21, 0.7383966445922852)]\n",
      "INFO flower 2022-04-08 21:10:22,575 | 2092374713.py:37 | Aggregated accuracy: 0.668908184224909 +- 0.06045241823390889\n",
      "DEBUG flower 2022-04-08 21:10:22,575 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:30,237 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:10:30,260 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:33,189 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:10:33,189 | 2092374713.py:15 | round-19-EVALUATION\n",
      "INFO flower 2022-04-08 21:10:33,192 | 2092374713.py:31 | [(1, 0.5928853750228882), (3, 0.6360152959823608), (5, 0.7145708799362183), (7, 0.5415019989013672), (9, 0.6518218517303467), (11, 0.6771653294563293), (13, 0.6818181872367859), (15, 0.7528957724571228), (17, 0.6785714030265808), (19, 0.7121211886405945), (21, 0.7426160573959351)]\n",
      "INFO flower 2022-04-08 21:10:33,193 | 2092374713.py:37 | Aggregated accuracy: 0.6710893945260481 +- 0.06037819554353087\n",
      "DEBUG flower 2022-04-08 21:10:33,194 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:40,842 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:10:40,865 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:43,744 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:10:43,745 | 2092374713.py:15 | round-20-EVALUATION\n",
      "INFO flower 2022-04-08 21:10:43,748 | 2092374713.py:31 | [(1, 0.6047430634498596), (3, 0.6398467421531677), (5, 0.7205588817596436), (7, 0.5415019989013672), (9, 0.6437246799468994), (11, 0.6850393414497375), (13, 0.6776859760284424), (15, 0.7528957724571228), (17, 0.682539701461792), (19, 0.7121211886405945), (21, 0.7299578189849854)]\n",
      "INFO flower 2022-04-08 21:10:43,748 | 2092374713.py:37 | Aggregated accuracy: 0.6718741059303284 +- 0.05844245405135229\n",
      "DEBUG flower 2022-04-08 21:10:43,749 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:51,407 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:10:51,430 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:10:54,360 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:10:54,360 | 2092374713.py:15 | round-21-EVALUATION\n",
      "INFO flower 2022-04-08 21:10:54,363 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6398467421531677), (5, 0.7165668606758118), (7, 0.5415019989013672), (9, 0.647773265838623), (11, 0.6850393414497375), (13, 0.6818181872367859), (15, 0.7528957724571228), (17, 0.6785714030265808), (19, 0.7196969985961914), (21, 0.7299578189849854)]\n",
      "INFO flower 2022-04-08 21:10:54,364 | 2092374713.py:37 | Aggregated accuracy: 0.6729421832344749 +- 0.05809257655155316\n",
      "DEBUG flower 2022-04-08 21:10:54,364 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:02,075 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:11:02,098 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:04,999 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:11:04,999 | 2092374713.py:15 | round-22-EVALUATION\n",
      "INFO flower 2022-04-08 21:11:05,002 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6398467421531677), (5, 0.71856290102005), (7, 0.5533596873283386), (9, 0.6396760940551758), (11, 0.6889764070510864), (13, 0.6818181872367859), (15, 0.7374517321586609), (17, 0.682539701461792), (19, 0.7462121248245239), (21, 0.7172995805740356)]\n",
      "INFO flower 2022-04-08 21:11:05,002 | 2092374713.py:37 | Aggregated accuracy: 0.6740398894656788 +- 0.0561030437846616\n",
      "DEBUG flower 2022-04-08 21:11:05,003 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:12,728 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:11:12,751 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:15,595 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:11:15,596 | 2092374713.py:15 | round-23-EVALUATION\n",
      "INFO flower 2022-04-08 21:11:15,598 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6398467421531677), (5, 0.7285429239273071), (7, 0.5573122501373291), (9, 0.6558704376220703), (11, 0.6929134130477905), (13, 0.6818181872367859), (15, 0.7528957724571228), (17, 0.6865079402923584), (19, 0.7462121248245239), (21, 0.7257384061813354)]\n",
      "INFO flower 2022-04-08 21:11:15,599 | 2092374713.py:37 | Aggregated accuracy: 0.6796685294671492 +- 0.05775227715693967\n",
      "DEBUG flower 2022-04-08 21:11:15,599 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:23,224 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:11:23,247 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:26,174 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:11:26,174 | 2092374713.py:15 | round-24-EVALUATION\n",
      "INFO flower 2022-04-08 21:11:26,177 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6398467421531677), (5, 0.7325349450111389), (7, 0.5533596873283386), (9, 0.659919023513794), (11, 0.6811023354530334), (13, 0.6859503984451294), (15, 0.7683397531509399), (17, 0.6984127163887024), (19, 0.7272727489471436), (21, 0.746835470199585)]\n",
      "INFO flower 2022-04-08 21:11:26,178 | 2092374713.py:37 | Aggregated accuracy: 0.6820244951681658 +- 0.060852805766964946\n",
      "DEBUG flower 2022-04-08 21:11:26,179 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:33,802 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:11:33,825 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:36,702 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:11:36,703 | 2092374713.py:15 | round-25-EVALUATION\n",
      "INFO flower 2022-04-08 21:11:36,705 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6475095748901367), (5, 0.7345309257507324), (7, 0.5612648129463196), (9, 0.659919023513794), (11, 0.6811023354530334), (13, 0.6776859760284424), (15, 0.760617733001709), (17, 0.6944444179534912), (19, 0.7348484992980957), (21, 0.7510548233985901)]\n",
      "INFO flower 2022-04-08 21:11:36,706 | 2092374713.py:37 | Aggregated accuracy: 0.6828794316811995 +- 0.05900325638648912\n",
      "DEBUG flower 2022-04-08 21:11:36,706 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:44,118 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:11:44,141 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:47,161 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:11:47,162 | 2092374713.py:15 | round-26-EVALUATION\n",
      "INFO flower 2022-04-08 21:11:47,165 | 2092374713.py:31 | [(1, 0.6086956262588501), (3, 0.6513410210609436), (5, 0.742514967918396), (7, 0.5494071245193481), (9, 0.6720647811889648), (11, 0.6811023354530334), (13, 0.6735537052154541), (15, 0.7644787430763245), (17, 0.6944444179534912), (19, 0.7386363744735718), (21, 0.746835470199585)]\n",
      "INFO flower 2022-04-08 21:11:47,166 | 2092374713.py:37 | Aggregated accuracy: 0.6839158697561785 +- 0.0618324995603031\n",
      "DEBUG flower 2022-04-08 21:11:47,166 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:54,703 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:11:54,727 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:11:57,723 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:11:57,723 | 2092374713.py:15 | round-27-EVALUATION\n",
      "INFO flower 2022-04-08 21:11:57,726 | 2092374713.py:31 | [(1, 0.6126482486724854), (3, 0.6551724076271057), (5, 0.7485029697418213), (7, 0.5375494360923767), (9, 0.659919023513794), (11, 0.6811023354530334), (13, 0.6735537052154541), (15, 0.7644787430763245), (17, 0.6984127163887024), (19, 0.7424242496490479), (21, 0.7594936490058899)]\n",
      "INFO flower 2022-04-08 21:11:57,726 | 2092374713.py:37 | Aggregated accuracy: 0.684841589494185 +- 0.0660697742084141\n",
      "DEBUG flower 2022-04-08 21:11:57,727 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:05,300 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:12:05,323 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:08,339 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:12:08,340 | 2092374713.py:15 | round-28-EVALUATION\n",
      "INFO flower 2022-04-08 21:12:08,342 | 2092374713.py:31 | [(1, 0.6166008114814758), (3, 0.6513410210609436), (5, 0.7544910311698914), (7, 0.5494071245193481), (9, 0.6639676094055176), (11, 0.6811023354530334), (13, 0.6694214940071106), (15, 0.760617733001709), (17, 0.7063491940498352), (19, 0.7462121248245239), (21, 0.7637130618095398)]\n",
      "INFO flower 2022-04-08 21:12:08,342 | 2092374713.py:37 | Aggregated accuracy: 0.6875657764348116 +- 0.06450520408843832\n",
      "DEBUG flower 2022-04-08 21:12:08,343 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:15,827 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:12:15,850 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:18,927 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:12:18,928 | 2092374713.py:15 | round-29-EVALUATION\n",
      "INFO flower 2022-04-08 21:12:18,930 | 2092374713.py:31 | [(1, 0.6205533742904663), (3, 0.6513410210609436), (5, 0.7564870119094849), (7, 0.5533596873283386), (9, 0.659919023513794), (11, 0.6850393414497375), (13, 0.6776859760284424), (15, 0.7644787430763245), (17, 0.7103174328804016), (19, 0.7537878751754761), (21, 0.7679324746131897)]\n",
      "INFO flower 2022-04-08 21:12:18,931 | 2092374713.py:37 | Aggregated accuracy: 0.6909910873933272 +- 0.06507408142898155\n",
      "DEBUG flower 2022-04-08 21:12:18,931 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:26,447 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:12:26,470 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:29,570 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:12:29,570 | 2092374713.py:15 | round-30-EVALUATION\n",
      "INFO flower 2022-04-08 21:12:29,573 | 2092374713.py:31 | [(1, 0.6284584999084473), (3, 0.6551724076271057), (5, 0.7644710540771484), (7, 0.5573122501373291), (9, 0.647773265838623), (11, 0.6850393414497375), (13, 0.6694214940071106), (15, 0.7644787430763245), (17, 0.7023809552192688), (19, 0.7537878751754761), (21, 0.7637130618095398)]\n",
      "INFO flower 2022-04-08 21:12:29,574 | 2092374713.py:37 | Aggregated accuracy: 0.6901826316660101 +- 0.06437531092854037\n",
      "DEBUG flower 2022-04-08 21:12:29,574 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:37,057 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:12:37,082 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:40,131 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:12:40,132 | 2092374713.py:15 | round-31-EVALUATION\n",
      "INFO flower 2022-04-08 21:12:40,134 | 2092374713.py:31 | [(1, 0.6324110627174377), (3, 0.6551724076271057), (5, 0.7604790329933167), (7, 0.5494071245193481), (9, 0.6396760940551758), (11, 0.6850393414497375), (13, 0.6694214940071106), (15, 0.760617733001709), (17, 0.6904761791229248), (19, 0.7651515007019043), (21, 0.7679324746131897)]\n",
      "INFO flower 2022-04-08 21:12:40,135 | 2092374713.py:37 | Aggregated accuracy: 0.6887076768008146 +- 0.06669715456196731\n",
      "DEBUG flower 2022-04-08 21:12:40,136 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:47,689 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:12:47,713 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:50,721 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:12:50,722 | 2092374713.py:15 | round-32-EVALUATION\n",
      "INFO flower 2022-04-08 21:12:50,724 | 2092374713.py:31 | [(1, 0.6324110627174377), (3, 0.6551724076271057), (5, 0.7764471173286438), (7, 0.5375494360923767), (9, 0.6680161952972412), (11, 0.6850393414497375), (13, 0.6694214940071106), (15, 0.7722007632255554), (17, 0.7023809552192688), (19, 0.7613636255264282), (21, 0.7679324746131897)]\n",
      "INFO flower 2022-04-08 21:12:50,724 | 2092374713.py:37 | Aggregated accuracy: 0.693448624827645 +- 0.07014320686266806\n",
      "DEBUG flower 2022-04-08 21:12:50,725 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:12:58,343 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:12:58,367 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:01,491 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:13:01,492 | 2092374713.py:15 | round-33-EVALUATION\n",
      "INFO flower 2022-04-08 21:13:01,494 | 2092374713.py:31 | [(1, 0.6284584999084473), (3, 0.6513410210609436), (5, 0.7744510769844055), (7, 0.52173912525177), (9, 0.6761133670806885), (11, 0.6732283234596252), (13, 0.6776859760284424), (15, 0.7683397531509399), (17, 0.7182539701461792), (19, 0.7424242496490479), (21, 0.7890295386314392)]\n",
      "INFO flower 2022-04-08 21:13:01,495 | 2092374713.py:37 | Aggregated accuracy: 0.6928240819410845 +- 0.07431760317219634\n",
      "DEBUG flower 2022-04-08 21:13:01,495 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:09,050 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:13:09,073 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:12,148 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:13:12,149 | 2092374713.py:15 | round-34-EVALUATION\n",
      "INFO flower 2022-04-08 21:13:12,151 | 2092374713.py:31 | [(1, 0.6324110627174377), (3, 0.6436781883239746), (5, 0.7784430980682373), (7, 0.52173912525177), (9, 0.6720647811889648), (11, 0.6732283234596252), (13, 0.6694214940071106), (15, 0.7722007632255554), (17, 0.7182539701461792), (19, 0.7424242496490479), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:13:12,152 | 2092374713.py:37 | Aggregated accuracy: 0.692848492752422 +- 0.0765068542173836\n",
      "DEBUG flower 2022-04-08 21:13:12,152 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:19,557 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:13:19,580 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:22,624 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:13:22,624 | 2092374713.py:15 | round-35-EVALUATION\n",
      "INFO flower 2022-04-08 21:13:22,627 | 2092374713.py:31 | [(1, 0.6363636255264282), (3, 0.6475095748901367), (5, 0.7804391384124756), (7, 0.52173912525177), (9, 0.6680161952972412), (11, 0.6732283234596252), (13, 0.6694214940071106), (15, 0.7722007632255554), (17, 0.7142857313156128), (19, 0.7462121248245239), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:13:22,627 | 2092374713.py:37 | Aggregated accuracy: 0.6933531327681108 +- 0.07645179369408346\n",
      "DEBUG flower 2022-04-08 21:13:22,628 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:30,120 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:13:30,144 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:33,181 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:13:33,181 | 2092374713.py:15 | round-36-EVALUATION\n",
      "INFO flower 2022-04-08 21:13:33,183 | 2092374713.py:31 | [(1, 0.6363636255264282), (3, 0.6436781883239746), (5, 0.7824351191520691), (7, 0.5335968136787415), (9, 0.6680161952972412), (11, 0.6771653294563293), (13, 0.6694214940071106), (15, 0.7722007632255554), (17, 0.7103174328804016), (19, 0.7651515007019043), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:13:33,184 | 2092374713.py:37 | Aggregated accuracy: 0.6959831660444086 +- 0.07572284996938047\n",
      "DEBUG flower 2022-04-08 21:13:33,184 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:40,697 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:13:40,719 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:43,723 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:13:43,723 | 2092374713.py:15 | round-37-EVALUATION\n",
      "INFO flower 2022-04-08 21:13:43,726 | 2092374713.py:31 | [(1, 0.6442687511444092), (3, 0.6360152959823608), (5, 0.7844311594963074), (7, 0.529644250869751), (9, 0.6639676094055176), (11, 0.6771653294563293), (13, 0.6735537052154541), (15, 0.7722007632255554), (17, 0.7142857313156128), (19, 0.7575757503509521), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:13:43,726 | 2092374713.py:37 | Aggregated accuracy: 0.6955069737000898 +- 0.07620480747674595\n",
      "DEBUG flower 2022-04-08 21:13:43,727 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:51,255 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:13:51,278 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:13:54,299 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:13:54,300 | 2092374713.py:15 | round-38-EVALUATION\n",
      "INFO flower 2022-04-08 21:13:54,302 | 2092374713.py:31 | [(1, 0.6521739363670349), (3, 0.6436781883239746), (5, 0.7844311594963074), (7, 0.52173912525177), (9, 0.6720647811889648), (11, 0.6850393414497375), (13, 0.6735537052154541), (15, 0.7722007632255554), (17, 0.7103174328804016), (19, 0.7613636255264282), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:13:54,303 | 2092374713.py:37 | Aggregated accuracy: 0.6976391293785789 +- 0.07662915932108216\n",
      "DEBUG flower 2022-04-08 21:13:54,303 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:01,730 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:14:01,753 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:04,762 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:14:04,763 | 2092374713.py:15 | round-39-EVALUATION\n",
      "INFO flower 2022-04-08 21:14:04,765 | 2092374713.py:31 | [(1, 0.6521739363670349), (3, 0.6513410210609436), (5, 0.7864271402359009), (7, 0.5256916880607605), (9, 0.6801619529724121), (11, 0.6811023354530334), (13, 0.6735537052154541), (15, 0.7760617733001709), (17, 0.7103174328804016), (19, 0.75), (21, 0.8016877770423889)]\n",
      "INFO flower 2022-04-08 21:14:04,766 | 2092374713.py:37 | Aggregated accuracy: 0.6989562511444092 +- 0.07548534256742141\n",
      "DEBUG flower 2022-04-08 21:14:04,767 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:12,186 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:14:12,209 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:15,117 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:14:15,118 | 2092374713.py:15 | round-40-EVALUATION\n",
      "INFO flower 2022-04-08 21:14:15,120 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6360152959823608), (5, 0.7904191613197327), (7, 0.5415019989013672), (9, 0.6720647811889648), (11, 0.6850393414497375), (13, 0.6694214940071106), (15, 0.7722007632255554), (17, 0.6984127163887024), (19, 0.7727272510528564), (21, 0.8016877770423889)]\n",
      "INFO flower 2022-04-08 21:14:15,121 | 2092374713.py:37 | Aggregated accuracy: 0.6999608765948903 +- 0.07493592256501938\n",
      "DEBUG flower 2022-04-08 21:14:15,122 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:22,675 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:14:22,699 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:25,604 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:14:25,604 | 2092374713.py:15 | round-41-EVALUATION\n",
      "INFO flower 2022-04-08 21:14:25,607 | 2092374713.py:31 | [(1, 0.6561264991760254), (3, 0.6321839094161987), (5, 0.7944111824035645), (7, 0.5415019989013672), (9, 0.692307710647583), (11, 0.6811023354530334), (13, 0.6776859760284424), (15, 0.7760617733001709), (17, 0.7142857313156128), (19, 0.7613636255264282), (21, 0.8016877770423889)]\n",
      "INFO flower 2022-04-08 21:14:25,607 | 2092374713.py:37 | Aggregated accuracy: 0.7026107744737105 +- 0.07476849061409954\n",
      "DEBUG flower 2022-04-08 21:14:25,608 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:33,182 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:14:33,206 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:36,131 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:14:36,131 | 2092374713.py:15 | round-42-EVALUATION\n",
      "INFO flower 2022-04-08 21:14:36,133 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6321839094161987), (5, 0.7984032034873962), (7, 0.5454545617103577), (9, 0.6801619529724121), (11, 0.6811023354530334), (13, 0.6776859760284424), (15, 0.7760617733001709), (17, 0.6984127163887024), (19, 0.7727272510528564), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:14:36,134 | 2092374713.py:37 | Aggregated accuracy: 0.7017946460030295 +- 0.07480313039794993\n",
      "DEBUG flower 2022-04-08 21:14:36,134 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:43,712 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:14:43,735 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:46,646 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:14:46,646 | 2092374713.py:15 | round-43-EVALUATION\n",
      "INFO flower 2022-04-08 21:14:46,649 | 2092374713.py:31 | [(1, 0.6561264991760254), (3, 0.6321839094161987), (5, 0.7944111824035645), (7, 0.5415019989013672), (9, 0.6963562965393066), (11, 0.6771653294563293), (13, 0.6776859760284424), (15, 0.7799227833747864), (17, 0.7023809552192688), (19, 0.7689393758773804), (21, 0.8101266026496887)]\n",
      "INFO flower 2022-04-08 21:14:46,649 | 2092374713.py:37 | Aggregated accuracy: 0.703345537185669 +- 0.07671808839052495\n",
      "DEBUG flower 2022-04-08 21:14:46,650 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:54,149 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:14:54,172 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:14:57,293 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:14:57,294 | 2092374713.py:15 | round-44-EVALUATION\n",
      "INFO flower 2022-04-08 21:14:57,296 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6321839094161987), (5, 0.7924151420593262), (7, 0.5415019989013672), (9, 0.7004048824310303), (11, 0.6850393414497375), (13, 0.6776859760284424), (15, 0.7837837934494019), (17, 0.6984127163887024), (19, 0.7727272510528564), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:14:57,297 | 2092374713.py:37 | Aggregated accuracy: 0.7053254626014016 +- 0.07725478561622917\n",
      "DEBUG flower 2022-04-08 21:14:57,298 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:04,905 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:15:04,927 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:07,842 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:15:07,843 | 2092374713.py:15 | round-45-EVALUATION\n",
      "INFO flower 2022-04-08 21:15:07,845 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6283524632453918), (5, 0.7984032034873962), (7, 0.5533596873283386), (9, 0.6842105388641357), (11, 0.6929134130477905), (13, 0.6694214940071106), (15, 0.7837837934494019), (17, 0.6944444179534912), (19, 0.7916666865348816), (21, 0.8016877770423889)]\n",
      "INFO flower 2022-04-08 21:15:07,846 | 2092374713.py:37 | Aggregated accuracy: 0.7056613727049394 +- 0.07644929902059495\n",
      "DEBUG flower 2022-04-08 21:15:07,846 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:15,283 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:15:15,307 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:18,292 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:15:18,292 | 2092374713.py:15 | round-46-EVALUATION\n",
      "INFO flower 2022-04-08 21:15:18,295 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6321839094161987), (5, 0.7984032034873962), (7, 0.5335968136787415), (9, 0.7004048824310303), (11, 0.6929134130477905), (13, 0.6735537052154541), (15, 0.7837837934494019), (17, 0.6984127163887024), (19, 0.7840909361839294), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:15:18,297 | 2092374713.py:37 | Aggregated accuracy: 0.7065244046124545 +- 0.08034923677983598\n",
      "DEBUG flower 2022-04-08 21:15:18,298 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:25,786 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:15:25,809 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:28,860 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:15:28,861 | 2092374713.py:15 | round-47-EVALUATION\n",
      "INFO flower 2022-04-08 21:15:28,863 | 2092374713.py:31 | [(1, 0.6521739363670349), (3, 0.6321839094161987), (5, 0.7924151420593262), (7, 0.5256916880607605), (9, 0.7044534683227539), (11, 0.6850393414497375), (13, 0.6776859760284424), (15, 0.7837837934494019), (17, 0.7063491940498352), (19, 0.7689393758773804), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:15:28,864 | 2092374713.py:37 | Aggregated accuracy: 0.7039147127758373 +- 0.08049335450649554\n",
      "DEBUG flower 2022-04-08 21:15:28,865 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:36,321 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:15:36,344 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:39,389 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:15:39,390 | 2092374713.py:15 | round-48-EVALUATION\n",
      "INFO flower 2022-04-08 21:15:39,392 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6283524632453918), (5, 0.7984032034873962), (7, 0.5454545617103577), (9, 0.6842105388641357), (11, 0.6968504190444946), (13, 0.6694214940071106), (15, 0.7837837934494019), (17, 0.6865079402923584), (19, 0.7878788113594055), (21, 0.8101266026496887)]\n",
      "INFO flower 2022-04-08 21:15:39,392 | 2092374713.py:37 | Aggregated accuracy: 0.7046426263722506 +- 0.07880010716461773\n",
      "DEBUG flower 2022-04-08 21:15:39,393 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:46,852 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:15:46,875 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:49,750 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:15:49,750 | 2092374713.py:15 | round-49-EVALUATION\n",
      "INFO flower 2022-04-08 21:15:49,752 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6245210766792297), (5, 0.8003991842269897), (7, 0.5494071245193481), (9, 0.6801619529724121), (11, 0.7007874250411987), (13, 0.6694214940071106), (15, 0.7837837934494019), (17, 0.6904761791229248), (19, 0.7840909361839294), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:15:49,753 | 2092374713.py:37 | Aggregated accuracy: 0.7052249312400818 +- 0.07881774010599195\n",
      "DEBUG flower 2022-04-08 21:15:49,754 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:15:57,434 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:15:57,457 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:00,282 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:16:00,283 | 2092374713.py:15 | round-50-EVALUATION\n",
      "INFO flower 2022-04-08 21:16:00,285 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6245210766792297), (5, 0.8083832263946533), (7, 0.5573122501373291), (9, 0.6761133670806885), (11, 0.7086614370346069), (13, 0.6735537052154541), (15, 0.7876448035240173), (17, 0.6785714030265808), (19, 0.7878788113594055), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:16:00,286 | 2092374713.py:37 | Aggregated accuracy: 0.7073652473363009 +- 0.07907665175132425\n",
      "DEBUG flower 2022-04-08 21:16:00,286 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:07,920 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:16:07,943 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:10,835 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:16:10,835 | 2092374713.py:15 | round-51-EVALUATION\n",
      "INFO flower 2022-04-08 21:16:10,838 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6245210766792297), (5, 0.802395224571228), (7, 0.5454545617103577), (9, 0.6801619529724121), (11, 0.7086614370346069), (13, 0.6735537052154541), (15, 0.7876448035240173), (17, 0.6865079402923584), (19, 0.7765151262283325), (21, 0.8101266026496887)]\n",
      "INFO flower 2022-04-08 21:16:10,839 | 2092374713.py:37 | Aggregated accuracy: 0.7050564993511547 +- 0.07885119999561942\n",
      "DEBUG flower 2022-04-08 21:16:10,839 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:18,248 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:16:18,271 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:21,300 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:16:21,301 | 2092374713.py:15 | round-52-EVALUATION\n",
      "INFO flower 2022-04-08 21:16:21,303 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6283524632453918), (5, 0.8003991842269897), (7, 0.5454545617103577), (9, 0.6761133670806885), (11, 0.712598443031311), (13, 0.6735537052154541), (15, 0.7837837934494019), (17, 0.682539701461792), (19, 0.7840909361839294), (21, 0.8016877770423889)]\n",
      "INFO flower 2022-04-08 21:16:21,304 | 2092374713.py:37 | Aggregated accuracy: 0.7044229995120656 +- 0.07783497779851857\n",
      "DEBUG flower 2022-04-08 21:16:21,304 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:28,694 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:16:28,717 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:31,783 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:16:31,784 | 2092374713.py:15 | round-53-EVALUATION\n",
      "INFO flower 2022-04-08 21:16:31,787 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6245210766792297), (5, 0.8043912053108215), (7, 0.5533596873283386), (9, 0.6761133670806885), (11, 0.712598443031311), (13, 0.6735537052154541), (15, 0.7876448035240173), (17, 0.6785714030265808), (19, 0.7840909361839294), (21, 0.797468364238739)]\n",
      "INFO flower 2022-04-08 21:16:31,787 | 2092374713.py:37 | Aggregated accuracy: 0.7051222378557379 +- 0.07701472635783634\n",
      "DEBUG flower 2022-04-08 21:16:31,788 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:39,189 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:16:39,212 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:42,270 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:16:42,271 | 2092374713.py:15 | round-54-EVALUATION\n",
      "INFO flower 2022-04-08 21:16:42,273 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6245210766792297), (5, 0.802395224571228), (7, 0.5533596873283386), (9, 0.6761133670806885), (11, 0.7047244310379028), (13, 0.6735537052154541), (15, 0.7876448035240173), (17, 0.6785714030265808), (19, 0.7840909361839294), (21, 0.8059071898460388)]\n",
      "INFO flower 2022-04-08 21:16:42,274 | 2092374713.py:37 | Aggregated accuracy: 0.7053514556451277 +- 0.07752767090932498\n",
      "DEBUG flower 2022-04-08 21:16:42,274 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:49,720 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:16:49,744 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:16:52,811 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:16:52,812 | 2092374713.py:15 | round-55-EVALUATION\n",
      "INFO flower 2022-04-08 21:16:52,814 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6245210766792297), (5, 0.8103792667388916), (7, 0.5652173757553101), (9, 0.6639676094055176), (11, 0.712598443031311), (13, 0.6735537052154541), (15, 0.7915058135986328), (17, 0.6746031641960144), (19, 0.7840909361839294), (21, 0.8185654282569885)]\n",
      "INFO flower 2022-04-08 21:16:52,815 | 2092374713.py:37 | Aggregated accuracy: 0.7079079096967523 +- 0.07902125893682278\n",
      "DEBUG flower 2022-04-08 21:16:52,816 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:00,442 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:17:00,465 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:03,542 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:17:03,542 | 2092374713.py:15 | round-56-EVALUATION\n",
      "INFO flower 2022-04-08 21:17:03,545 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.8083832263946533), (7, 0.5849802494049072), (9, 0.647773265838623), (11, 0.7204724550247192), (13, 0.6611570119857788), (15, 0.7915058135986328), (17, 0.658730149269104), (19, 0.8030303120613098), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:17:03,545 | 2092374713.py:37 | Aggregated accuracy: 0.7093094804070212 +- 0.0783063970821014\n",
      "DEBUG flower 2022-04-08 21:17:03,546 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:11,024 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:17:11,047 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:14,091 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:17:14,092 | 2092374713.py:15 | round-57-EVALUATION\n",
      "INFO flower 2022-04-08 21:17:14,094 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6206896305084229), (5, 0.8043912053108215), (7, 0.5612648129463196), (9, 0.6842105388641357), (11, 0.6929134130477905), (13, 0.6694214940071106), (15, 0.7876448035240173), (17, 0.682539701461792), (19, 0.7689393758773804), (21, 0.8227847814559937)]\n",
      "INFO flower 2022-04-08 21:17:14,095 | 2092374713.py:37 | Aggregated accuracy: 0.7049889835444364 +- 0.07793049810789707\n",
      "DEBUG flower 2022-04-08 21:17:14,095 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:21,553 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:17:21,576 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:24,514 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:17:24,514 | 2092374713.py:15 | round-58-EVALUATION\n",
      "INFO flower 2022-04-08 21:17:24,516 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6245210766792297), (5, 0.8063872456550598), (7, 0.5652173757553101), (9, 0.6558704376220703), (11, 0.7086614370346069), (13, 0.6694214940071106), (15, 0.799227774143219), (17, 0.670634925365448), (19, 0.7840909361839294), (21, 0.8227847814559937)]\n",
      "INFO flower 2022-04-08 21:17:24,517 | 2092374713.py:37 | Aggregated accuracy: 0.7068001519549977 +- 0.08062897622830033\n",
      "DEBUG flower 2022-04-08 21:17:24,518 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:32,180 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:17:32,202 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:35,120 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:17:35,121 | 2092374713.py:15 | round-59-EVALUATION\n",
      "INFO flower 2022-04-08 21:17:35,123 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6283524632453918), (5, 0.8003991842269897), (7, 0.5612648129463196), (9, 0.6801619529724121), (11, 0.6968504190444946), (13, 0.6735537052154541), (15, 0.7876448035240173), (17, 0.6746031641960144), (19, 0.7803030014038086), (21, 0.8143460154533386)]\n",
      "INFO flower 2022-04-08 21:17:35,123 | 2092374713.py:37 | Aggregated accuracy: 0.705591922456568 +- 0.0764934013255644\n",
      "DEBUG flower 2022-04-08 21:17:35,124 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:42,652 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:17:42,676 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:45,557 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:17:45,557 | 2092374713.py:15 | round-60-EVALUATION\n",
      "INFO flower 2022-04-08 21:17:45,559 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6283524632453918), (5, 0.8043912053108215), (7, 0.5691699385643005), (9, 0.6639676094055176), (11, 0.7007874250411987), (13, 0.6694214940071106), (15, 0.7876448035240173), (17, 0.670634925365448), (19, 0.7878788113594055), (21, 0.8101266026496887)]\n",
      "INFO flower 2022-04-08 21:17:45,560 | 2092374713.py:37 | Aggregated accuracy: 0.7054872241887179 +- 0.07655638213093494\n",
      "DEBUG flower 2022-04-08 21:17:45,560 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:52,998 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:17:53,021 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:17:56,047 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:17:56,047 | 2092374713.py:15 | round-61-EVALUATION\n",
      "INFO flower 2022-04-08 21:17:56,050 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6283524632453918), (5, 0.8063872456550598), (7, 0.5691699385643005), (9, 0.6680161952972412), (11, 0.7007874250411987), (13, 0.6694214940071106), (15, 0.7953668236732483), (17, 0.670634925365448), (19, 0.7803030014038086), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:17:56,050 | 2092374713.py:37 | Aggregated accuracy: 0.7075843540104952 +- 0.07888702565665766\n",
      "DEBUG flower 2022-04-08 21:17:56,050 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:03,491 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:18:03,515 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:06,575 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:18:06,575 | 2092374713.py:15 | round-62-EVALUATION\n",
      "INFO flower 2022-04-08 21:18:06,578 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.8123752474784851), (7, 0.5770751237869263), (9, 0.6558704376220703), (11, 0.712598443031311), (13, 0.6735537052154541), (15, 0.799227774143219), (17, 0.6666666865348816), (19, 0.7916666865348816), (21, 0.8185654282569885)]\n",
      "INFO flower 2022-04-08 21:18:06,578 | 2092374713.py:37 | Aggregated accuracy: 0.7105157050219449 +- 0.07858176802195702\n",
      "DEBUG flower 2022-04-08 21:18:06,579 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:13,997 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:18:14,020 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:17,061 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:18:17,061 | 2092374713.py:15 | round-63-EVALUATION\n",
      "INFO flower 2022-04-08 21:18:17,064 | 2092374713.py:31 | [(1, 0.6521739363670349), (3, 0.6206896305084229), (5, 0.8063872456550598), (7, 0.5533596873283386), (9, 0.6963562965393066), (11, 0.6929134130477905), (13, 0.6735537052154541), (15, 0.7915058135986328), (17, 0.6785714030265808), (19, 0.7613636255264282), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:18:17,064 | 2092374713.py:37 | Aggregated accuracy: 0.7060488354076039 +- 0.08194405687448711\n",
      "DEBUG flower 2022-04-08 21:18:17,064 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:24,558 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:18:24,581 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:27,639 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:18:27,640 | 2092374713.py:15 | round-64-EVALUATION\n",
      "INFO flower 2022-04-08 21:18:27,642 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.8083832263946533), (7, 0.573122501373291), (9, 0.6720647811889648), (11, 0.7047244310379028), (13, 0.6735537052154541), (15, 0.799227774143219), (17, 0.6626983880996704), (19, 0.7878788113594055), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:18:27,643 | 2092374713.py:37 | Aggregated accuracy: 0.7109954953193665 +- 0.07941676365565446\n",
      "DEBUG flower 2022-04-08 21:18:27,643 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:35,129 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:18:35,154 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:38,020 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:18:38,021 | 2092374713.py:15 | round-65-EVALUATION\n",
      "INFO flower 2022-04-08 21:18:38,023 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.8123752474784851), (7, 0.5810276865959167), (9, 0.659919023513794), (11, 0.712598443031311), (13, 0.6694214940071106), (15, 0.7953668236732483), (17, 0.6626983880996704), (19, 0.7954545617103577), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:18:38,024 | 2092374713.py:37 | Aggregated accuracy: 0.7116265134377913 +- 0.07904496777446268\n",
      "DEBUG flower 2022-04-08 21:18:38,024 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:45,654 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:18:45,677 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:48,583 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:18:48,583 | 2092374713.py:15 | round-66-EVALUATION\n",
      "INFO flower 2022-04-08 21:18:48,585 | 2092374713.py:31 | [(1, 0.6837944388389587), (3, 0.6360152959823608), (5, 0.8103792667388916), (7, 0.5810276865959167), (9, 0.659919023513794), (11, 0.7165354490280151), (13, 0.6694214940071106), (15, 0.7915058135986328), (17, 0.64682537317276), (19, 0.7992424368858337), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:18:48,586 | 2092374713.py:37 | Aggregated accuracy: 0.711060952056538 +- 0.07939761701111665\n",
      "DEBUG flower 2022-04-08 21:18:48,586 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:56,236 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:18:56,259 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:18:59,218 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:18:59,218 | 2092374713.py:15 | round-67-EVALUATION\n",
      "INFO flower 2022-04-08 21:18:59,221 | 2092374713.py:31 | [(1, 0.6837944388389587), (3, 0.6360152959823608), (5, 0.8083832263946533), (7, 0.5928853750228882), (9, 0.6558704376220703), (11, 0.7165354490280151), (13, 0.6694214940071106), (15, 0.7953668236732483), (17, 0.6388888955116272), (19, 0.7992424368858337), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:18:59,222 | 2092374713.py:37 | Aggregated accuracy: 0.7112189152024009 +- 0.0787152715538974\n",
      "DEBUG flower 2022-04-08 21:18:59,223 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:06,804 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:19:06,827 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:09,864 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:19:09,865 | 2092374713.py:15 | round-68-EVALUATION\n",
      "INFO flower 2022-04-08 21:19:09,868 | 2092374713.py:31 | [(1, 0.6837944388389587), (3, 0.6321839094161987), (5, 0.8103792667388916), (7, 0.5770751237869263), (9, 0.6680161952972412), (11, 0.712598443031311), (13, 0.6735537052154541), (15, 0.7953668236732483), (17, 0.64682537317276), (19, 0.7992424368858337), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:19:09,868 | 2092374713.py:37 | Aggregated accuracy: 0.7114581736651334 +- 0.08005347790043779\n",
      "DEBUG flower 2022-04-08 21:19:09,869 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:17,256 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:19:17,279 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:20,377 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:19:20,377 | 2092374713.py:15 | round-69-EVALUATION\n",
      "INFO flower 2022-04-08 21:19:20,380 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.8063872456550598), (7, 0.5810276865959167), (9, 0.6680161952972412), (11, 0.7086614370346069), (13, 0.6735537052154541), (15, 0.7953668236732483), (17, 0.64682537317276), (19, 0.7954545617103577), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:19:20,380 | 2092374713.py:37 | Aggregated accuracy: 0.7108008428053423 +- 0.0800828617664724\n",
      "DEBUG flower 2022-04-08 21:19:20,381 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:27,812 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:19:27,834 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:30,866 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:19:30,866 | 2092374713.py:15 | round-70-EVALUATION\n",
      "INFO flower 2022-04-08 21:19:30,868 | 2092374713.py:31 | [(1, 0.6837944388389587), (3, 0.6283524632453918), (5, 0.8063872456550598), (7, 0.5849802494049072), (9, 0.6558704376220703), (11, 0.7204724550247192), (13, 0.6694214940071106), (15, 0.799227774143219), (17, 0.6309523582458496), (19, 0.7992424368858337), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:19:30,869 | 2092374713.py:37 | Aggregated accuracy: 0.7096095952120695 +- 0.08136474031399793\n",
      "DEBUG flower 2022-04-08 21:19:30,869 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:38,272 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:19:38,296 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:41,207 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:19:41,208 | 2092374713.py:15 | round-71-EVALUATION\n",
      "INFO flower 2022-04-08 21:19:41,211 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6283524632453918), (5, 0.8123752474784851), (7, 0.5810276865959167), (9, 0.6639676094055176), (11, 0.7165354490280151), (13, 0.6735537052154541), (15, 0.799227774143219), (17, 0.6349206566810608), (19, 0.7954545617103577), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:19:41,212 | 2092374713.py:37 | Aggregated accuracy: 0.7109727317636664 +- 0.08246593547212054\n",
      "DEBUG flower 2022-04-08 21:19:41,212 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:48,925 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:19:48,948 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:51,836 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:19:51,837 | 2092374713.py:15 | round-72-EVALUATION\n",
      "INFO flower 2022-04-08 21:19:51,839 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6283524632453918), (5, 0.8063872456550598), (7, 0.5928853750228882), (9, 0.6558704376220703), (11, 0.7204724550247192), (13, 0.6735537052154541), (15, 0.799227774143219), (17, 0.6269841194152832), (19, 0.7992424368858337), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:19:51,840 | 2092374713.py:37 | Aggregated accuracy: 0.7103674086657438 +- 0.08116274678757321\n",
      "DEBUG flower 2022-04-08 21:19:51,840 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:19:59,411 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:19:59,433 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:02,459 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:20:02,460 | 2092374713.py:15 | round-73-EVALUATION\n",
      "INFO flower 2022-04-08 21:20:02,463 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.8063872456550598), (7, 0.5928853750228882), (9, 0.659919023513794), (11, 0.7244094610214233), (13, 0.6735537052154541), (15, 0.799227774143219), (17, 0.6230158805847168), (19, 0.8030303120613098), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:20:02,463 | 2092374713.py:37 | Aggregated accuracy: 0.7117735960266807 +- 0.08105928641986303\n",
      "DEBUG flower 2022-04-08 21:20:02,464 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:09,952 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:20:09,975 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:13,015 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:20:13,016 | 2092374713.py:15 | round-74-EVALUATION\n",
      "INFO flower 2022-04-08 21:20:13,019 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6321839094161987), (5, 0.7984032034873962), (7, 0.573122501373291), (9, 0.6842105388641357), (11, 0.6968504190444946), (13, 0.6818181872367859), (15, 0.7953668236732483), (17, 0.64682537317276), (19, 0.7765151262283325), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:20:13,020 | 2092374713.py:37 | Aggregated accuracy: 0.7088329195976257 +- 0.07955308496282598\n",
      "DEBUG flower 2022-04-08 21:20:13,020 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:20,547 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:20:20,570 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:23,594 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:20:23,594 | 2092374713.py:15 | round-75-EVALUATION\n",
      "INFO flower 2022-04-08 21:20:23,596 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.8083832263946533), (7, 0.5928853750228882), (9, 0.6639676094055176), (11, 0.7165354490280151), (13, 0.6776859760284424), (15, 0.7953668236732483), (17, 0.6269841194152832), (19, 0.7916666865348816), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:20:23,597 | 2092374713.py:37 | Aggregated accuracy: 0.711343223398382 +- 0.07951495908921713\n",
      "DEBUG flower 2022-04-08 21:20:23,597 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:31,033 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:20:31,055 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:34,117 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:20:34,117 | 2092374713.py:15 | round-76-EVALUATION\n",
      "INFO flower 2022-04-08 21:20:34,119 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.8043912053108215), (7, 0.5968379378318787), (9, 0.6639676094055176), (11, 0.712598443031311), (13, 0.6735537052154541), (15, 0.7876448035240173), (17, 0.6309523582458496), (19, 0.7954545617103577), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:20:34,120 | 2092374713.py:37 | Aggregated accuracy: 0.7098772742531516 +- 0.0776993027773118\n",
      "DEBUG flower 2022-04-08 21:20:34,120 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:41,547 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:20:41,570 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:44,434 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:20:44,434 | 2092374713.py:15 | round-77-EVALUATION\n",
      "INFO flower 2022-04-08 21:20:44,436 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6321839094161987), (5, 0.796407163143158), (7, 0.5691699385643005), (9, 0.6842105388641357), (11, 0.6929134130477905), (13, 0.6776859760284424), (15, 0.7953668236732483), (17, 0.64682537317276), (19, 0.7765151262283325), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:20:44,437 | 2092374713.py:37 | Aggregated accuracy: 0.7075585722923279 +- 0.08016051666837934\n",
      "DEBUG flower 2022-04-08 21:20:44,437 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:51,978 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:20:52,001 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:20:54,983 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:20:54,983 | 2092374713.py:15 | round-78-EVALUATION\n",
      "INFO flower 2022-04-08 21:20:54,986 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.802395224571228), (7, 0.5928853750228882), (9, 0.6720647811889648), (11, 0.7086614370346069), (13, 0.6776859760284424), (15, 0.7915058135986328), (17, 0.6309523582458496), (19, 0.7878788113594055), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:20:54,987 | 2092374713.py:37 | Aggregated accuracy: 0.7098011699589816 +- 0.078630716128201\n",
      "DEBUG flower 2022-04-08 21:20:54,988 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:02,710 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:21:02,734 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:05,613 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:21:05,614 | 2092374713.py:15 | round-79-EVALUATION\n",
      "INFO flower 2022-04-08 21:21:05,616 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.796407163143158), (7, 0.6007905006408691), (9, 0.6639676094055176), (11, 0.7204724550247192), (13, 0.6735537052154541), (15, 0.7915058135986328), (17, 0.6269841194152832), (19, 0.7992424368858337), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:21:05,617 | 2092374713.py:37 | Aggregated accuracy: 0.7105611996217207 +- 0.07752155115291107\n",
      "DEBUG flower 2022-04-08 21:21:05,617 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:13,074 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:21:13,098 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:16,165 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:21:16,165 | 2092374713.py:15 | round-80-EVALUATION\n",
      "INFO flower 2022-04-08 21:21:16,168 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.8003991842269897), (7, 0.6007905006408691), (9, 0.659919023513794), (11, 0.7204724550247192), (13, 0.6776859760284424), (15, 0.799227774143219), (17, 0.6269841194152832), (19, 0.810606062412262), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:21:16,168 | 2092374713.py:37 | Aggregated accuracy: 0.712631496516141 +- 0.0790469191266901\n",
      "DEBUG flower 2022-04-08 21:21:16,169 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:23,634 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:21:23,658 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:26,726 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:21:26,727 | 2092374713.py:15 | round-81-EVALUATION\n",
      "INFO flower 2022-04-08 21:21:26,729 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6360152959823608), (5, 0.7984032034873962), (7, 0.6086956262588501), (9, 0.6639676094055176), (11, 0.7165354490280151), (13, 0.6776859760284424), (15, 0.7915058135986328), (17, 0.6309523582458496), (19, 0.8030303120613098), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:21:26,730 | 2092374713.py:37 | Aggregated accuracy: 0.7121731422164224 +- 0.0763427964697374\n",
      "DEBUG flower 2022-04-08 21:21:26,730 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:34,210 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:21:34,233 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:37,301 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:21:37,301 | 2092374713.py:15 | round-82-EVALUATION\n",
      "INFO flower 2022-04-08 21:21:37,304 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6360152959823608), (5, 0.796407163143158), (7, 0.6086956262588501), (9, 0.659919023513794), (11, 0.7204724550247192), (13, 0.6818181872367859), (15, 0.799227774143219), (17, 0.6230158805847168), (19, 0.8068181872367859), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:21:37,305 | 2092374713.py:37 | Aggregated accuracy: 0.7126820466735146 +- 0.07821629121959725\n",
      "DEBUG flower 2022-04-08 21:21:37,305 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:44,675 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:21:44,699 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:47,588 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:21:47,588 | 2092374713.py:15 | round-83-EVALUATION\n",
      "INFO flower 2022-04-08 21:21:47,591 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.7984032034873962), (7, 0.6047430634498596), (9, 0.6680161952972412), (11, 0.712598443031311), (13, 0.6776859760284424), (15, 0.799227774143219), (17, 0.6269841194152832), (19, 0.7992424368858337), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:21:47,591 | 2092374713.py:37 | Aggregated accuracy: 0.7134147232229059 +- 0.08167288916106505\n",
      "DEBUG flower 2022-04-08 21:21:47,592 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:55,280 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:21:55,302 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:21:58,123 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:21:58,123 | 2092374713.py:15 | round-84-EVALUATION\n",
      "INFO flower 2022-04-08 21:21:58,126 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6283524632453918), (5, 0.796407163143158), (7, 0.5968379378318787), (9, 0.6801619529724121), (11, 0.7007874250411987), (13, 0.6776859760284424), (15, 0.7915058135986328), (17, 0.6349206566810608), (19, 0.7916666865348816), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:21:58,126 | 2092374713.py:37 | Aggregated accuracy: 0.7111439542336897 +- 0.07954226419332054\n",
      "DEBUG flower 2022-04-08 21:21:58,127 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:05,617 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:22:05,640 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:08,652 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:22:08,652 | 2092374713.py:15 | round-85-EVALUATION\n",
      "INFO flower 2022-04-08 21:22:08,654 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6283524632453918), (5, 0.7924151420593262), (7, 0.6047430634498596), (9, 0.659919023513794), (11, 0.7244094610214233), (13, 0.6776859760284424), (15, 0.7876448035240173), (17, 0.6309523582458496), (19, 0.8068181872367859), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:22:08,655 | 2092374713.py:37 | Aggregated accuracy: 0.7105546214363792 +- 0.07751195115708528\n",
      "DEBUG flower 2022-04-08 21:22:08,656 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:16,161 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:22:16,184 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:19,243 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:22:19,243 | 2092374713.py:15 | round-86-EVALUATION\n",
      "INFO flower 2022-04-08 21:22:19,246 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6047430634498596), (9, 0.659919023513794), (11, 0.7283464670181274), (13, 0.6818181872367859), (15, 0.7876448035240173), (17, 0.6269841194152832), (19, 0.814393937587738), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:22:19,246 | 2092374713.py:37 | Aggregated accuracy: 0.7126963463696566 +- 0.07857084910482766\n",
      "DEBUG flower 2022-04-08 21:22:19,247 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:26,670 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:22:26,692 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:29,784 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:22:29,785 | 2092374713.py:15 | round-87-EVALUATION\n",
      "INFO flower 2022-04-08 21:22:29,787 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6398467421531677), (5, 0.7984032034873962), (7, 0.6047430634498596), (9, 0.6720647811889648), (11, 0.7283464670181274), (13, 0.6859503984451294), (15, 0.799227774143219), (17, 0.6230158805847168), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:22:29,788 | 2092374713.py:37 | Aggregated accuracy: 0.7161054448647932 +- 0.07987236646722741\n",
      "DEBUG flower 2022-04-08 21:22:29,789 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:37,248 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:22:37,271 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:40,225 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:22:40,226 | 2092374713.py:15 | round-88-EVALUATION\n",
      "INFO flower 2022-04-08 21:22:40,228 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.796407163143158), (7, 0.6047430634498596), (9, 0.6680161952972412), (11, 0.7244094610214233), (13, 0.6859503984451294), (15, 0.799227774143219), (17, 0.6269841194152832), (19, 0.810606062412262), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:22:40,229 | 2092374713.py:37 | Aggregated accuracy: 0.7160913619128141 +- 0.08237314639328022\n",
      "DEBUG flower 2022-04-08 21:22:40,229 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:47,771 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:22:47,795 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:50,690 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:22:50,691 | 2092374713.py:15 | round-89-EVALUATION\n",
      "INFO flower 2022-04-08 21:22:50,694 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.796407163143158), (7, 0.6086956262588501), (9, 0.659919023513794), (11, 0.7244094610214233), (13, 0.6818181872367859), (15, 0.799227774143219), (17, 0.6269841194152832), (19, 0.814393937587738), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:22:50,694 | 2092374713.py:37 | Aggregated accuracy: 0.7149161100387573 +- 0.08163127441100654\n",
      "DEBUG flower 2022-04-08 21:22:50,695 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:22:58,335 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:22:58,360 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:01,435 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:23:01,435 | 2092374713.py:15 | round-90-EVALUATION\n",
      "INFO flower 2022-04-08 21:23:01,437 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.802395224571228), (7, 0.6166008114814758), (9, 0.6558704376220703), (11, 0.7401574850082397), (13, 0.6818181872367859), (15, 0.7953668236732483), (17, 0.6071428656578064), (19, 0.8333333134651184), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:23:01,438 | 2092374713.py:37 | Aggregated accuracy: 0.7167612151666121 +- 0.08434050214358957\n",
      "DEBUG flower 2022-04-08 21:23:01,439 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:08,921 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:23:08,944 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:12,020 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:23:12,020 | 2092374713.py:15 | round-91-EVALUATION\n",
      "INFO flower 2022-04-08 21:23:12,023 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6206896305084229), (5, 0.7944111824035645), (7, 0.5968379378318787), (9, 0.6720647811889648), (11, 0.7086614370346069), (13, 0.6776859760284424), (15, 0.799227774143219), (17, 0.6309523582458496), (19, 0.7954545617103577), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:23:12,023 | 2092374713.py:37 | Aggregated accuracy: 0.7105718634345315 +- 0.08197661690733422\n",
      "DEBUG flower 2022-04-08 21:23:12,024 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:19,438 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:23:19,460 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:22,548 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:23:22,548 | 2092374713.py:15 | round-92-EVALUATION\n",
      "INFO flower 2022-04-08 21:23:22,551 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6283524632453918), (5, 0.8003991842269897), (7, 0.6086956262588501), (9, 0.6558704376220703), (11, 0.7204724550247192), (13, 0.6859503984451294), (15, 0.799227774143219), (17, 0.6309523582458496), (19, 0.814393937587738), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:23:22,551 | 2092374713.py:37 | Aggregated accuracy: 0.7160676392641935 +- 0.08315360925747653\n",
      "DEBUG flower 2022-04-08 21:23:22,552 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:30,055 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:23:30,078 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:32,977 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:23:32,978 | 2092374713.py:15 | round-93-EVALUATION\n",
      "INFO flower 2022-04-08 21:23:32,980 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6206896305084229), (5, 0.796407163143158), (7, 0.5928853750228882), (9, 0.6639676094055176), (11, 0.712598443031311), (13, 0.6818181872367859), (15, 0.7876448035240173), (17, 0.6428571343421936), (19, 0.8068181872367859), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:23:32,981 | 2092374713.py:37 | Aggregated accuracy: 0.7114295038309965 +- 0.08117727755412787\n",
      "DEBUG flower 2022-04-08 21:23:32,981 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:40,579 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:23:40,602 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:43,519 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:23:43,520 | 2092374713.py:15 | round-94-EVALUATION\n",
      "INFO flower 2022-04-08 21:23:43,522 | 2092374713.py:31 | [(1, 0.6521739363670349), (3, 0.6168582439422607), (5, 0.7904191613197327), (7, 0.5849802494049072), (9, 0.6842105388641357), (11, 0.712598443031311), (13, 0.6776859760284424), (15, 0.7915058135986328), (17, 0.6428571343421936), (19, 0.7954545617103577), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:23:43,523 | 2092374713.py:37 | Aggregated accuracy: 0.7091877026991411 +- 0.08231548167513465\n",
      "DEBUG flower 2022-04-08 21:23:43,523 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:51,023 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:23:51,047 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:23:54,088 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:23:54,088 | 2092374713.py:15 | round-95-EVALUATION\n",
      "INFO flower 2022-04-08 21:23:54,091 | 2092374713.py:31 | [(1, 0.6561264991760254), (3, 0.6206896305084229), (5, 0.7884231805801392), (7, 0.5770751237869263), (9, 0.6801619529724121), (11, 0.7086614370346069), (13, 0.6818181872367859), (15, 0.799227774143219), (17, 0.64682537317276), (19, 0.7878788113594055), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:23:54,091 | 2092374713.py:37 | Aggregated accuracy: 0.709402550350536 +- 0.08305093602471816\n",
      "DEBUG flower 2022-04-08 21:23:54,092 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:01,570 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:24:01,593 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:04,631 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:24:04,632 | 2092374713.py:15 | round-96-EVALUATION\n",
      "INFO flower 2022-04-08 21:24:04,634 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6245210766792297), (5, 0.7904191613197327), (7, 0.5928853750228882), (9, 0.6842105388641357), (11, 0.712598443031311), (13, 0.6776859760284424), (15, 0.7953668236732483), (17, 0.6230158805847168), (19, 0.7992424368858337), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-08 21:24:04,635 | 2092374713.py:37 | Aggregated accuracy: 0.7117232951250944 +- 0.08427368749038701\n",
      "DEBUG flower 2022-04-08 21:24:04,635 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:12,127 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:24:12,150 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:15,225 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:24:15,225 | 2092374713.py:15 | round-97-EVALUATION\n",
      "INFO flower 2022-04-08 21:24:15,228 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6283524632453918), (5, 0.7944111824035645), (7, 0.6007905006408691), (9, 0.6558704376220703), (11, 0.7244094610214233), (13, 0.6859503984451294), (15, 0.799227774143219), (17, 0.60317462682724), (19, 0.8257575631141663), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:24:15,228 | 2092374713.py:37 | Aggregated accuracy: 0.7118009491400286 +- 0.08626669906407823\n",
      "DEBUG flower 2022-04-08 21:24:15,229 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:22,654 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:24:22,677 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:25,549 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:24:25,549 | 2092374713.py:15 | round-98-EVALUATION\n",
      "INFO flower 2022-04-08 21:24:25,552 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6360152959823608), (5, 0.7944111824035645), (7, 0.6126482486724854), (9, 0.659919023513794), (11, 0.7283464670181274), (13, 0.6859503984451294), (15, 0.799227774143219), (17, 0.5992063283920288), (19, 0.8295454382896423), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:24:25,552 | 2092374713.py:37 | Aggregated accuracy: 0.7139015251939947 +- 0.08444342228308904\n",
      "DEBUG flower 2022-04-08 21:24:25,553 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:33,106 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:24:33,129 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:35,989 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:24:35,989 | 2092374713.py:15 | round-99-EVALUATION\n",
      "INFO flower 2022-04-08 21:24:35,992 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6283524632453918), (5, 0.8003991842269897), (7, 0.6166008114814758), (9, 0.659919023513794), (11, 0.7283464670181274), (13, 0.6859503984451294), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:24:35,992 | 2092374713.py:37 | Aggregated accuracy: 0.7138032642277804 +- 0.08704149968616341\n",
      "DEBUG flower 2022-04-08 21:24:35,993 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:43,524 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:24:43,547 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:46,600 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:24:46,601 | 2092374713.py:15 | round-100-EVALUATION\n",
      "INFO flower 2022-04-08 21:24:46,603 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6283524632453918), (5, 0.796407163143158), (7, 0.6126482486724854), (9, 0.659919023513794), (11, 0.7283464670181274), (13, 0.6859503984451294), (15, 0.7953668236732483), (17, 0.5992063283920288), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:24:46,606 | 2092374713.py:37 | Aggregated accuracy: 0.7138025272976268 +- 0.08611041575957647\n",
      "DEBUG flower 2022-04-08 21:24:46,607 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:54,062 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:24:54,086 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:24:57,202 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:24:57,202 | 2092374713.py:15 | round-101-EVALUATION\n",
      "INFO flower 2022-04-08 21:24:57,205 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.802395224571228), (7, 0.6205533742904663), (9, 0.659919023513794), (11, 0.7322834730148315), (13, 0.6859503984451294), (15, 0.8030887842178345), (17, 0.5873016119003296), (19, 0.8333333134651184), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:24:57,205 | 2092374713.py:37 | Aggregated accuracy: 0.7157116098837419 +- 0.08744961957029317\n",
      "DEBUG flower 2022-04-08 21:24:57,205 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:04,788 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:25:04,810 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:07,728 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:25:07,729 | 2092374713.py:15 | round-102-EVALUATION\n",
      "INFO flower 2022-04-08 21:25:07,731 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6436781883239746), (5, 0.802395224571228), (7, 0.6166008114814758), (9, 0.647773265838623), (11, 0.7362204790115356), (13, 0.6859503984451294), (15, 0.799227774143219), (17, 0.5873016119003296), (19, 0.8371211886405945), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:25:07,732 | 2092374713.py:37 | Aggregated accuracy: 0.716387228532271 +- 0.08829699448376889\n",
      "DEBUG flower 2022-04-08 21:25:07,732 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:15,406 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:25:15,429 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:18,307 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:25:18,307 | 2092374713.py:15 | round-103-EVALUATION\n",
      "INFO flower 2022-04-08 21:25:18,309 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6283524632453918), (5, 0.802395224571228), (7, 0.6126482486724854), (9, 0.6558704376220703), (11, 0.7283464670181274), (13, 0.6859503984451294), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.8295454382896423), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:25:18,310 | 2092374713.py:37 | Aggregated accuracy: 0.714383835142309 +- 0.08888829085480814\n",
      "DEBUG flower 2022-04-08 21:25:18,310 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:25,746 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:25:25,769 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:28,862 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:25:28,862 | 2092374713.py:15 | round-104-EVALUATION\n",
      "INFO flower 2022-04-08 21:25:28,864 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.8003991842269897), (7, 0.6126482486724854), (9, 0.6558704376220703), (11, 0.7283464670181274), (13, 0.6859503984451294), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.8371211886405945), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:25:28,865 | 2092374713.py:37 | Aggregated accuracy: 0.7155987186865373 +- 0.0891304346386918\n",
      "DEBUG flower 2022-04-08 21:25:28,865 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:36,368 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:25:36,391 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:39,460 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:25:39,460 | 2092374713.py:15 | round-105-EVALUATION\n",
      "INFO flower 2022-04-08 21:25:39,462 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6206896305084229), (5, 0.7944111824035645), (7, 0.6047430634498596), (9, 0.6680161952972412), (11, 0.7244094610214233), (13, 0.6983470916748047), (15, 0.799227774143219), (17, 0.5992063283920288), (19, 0.8181818127632141), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-08 21:25:39,463 | 2092374713.py:37 | Aggregated accuracy: 0.7142039158127524 +- 0.08850473283623654\n",
      "DEBUG flower 2022-04-08 21:25:39,464 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:46,933 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:25:46,955 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:49,868 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:25:49,869 | 2092374713.py:15 | round-106-EVALUATION\n",
      "INFO flower 2022-04-08 21:25:49,871 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6245210766792297), (5, 0.796407163143158), (7, 0.6086956262588501), (9, 0.6558704376220703), (11, 0.7244094610214233), (13, 0.6900826692581177), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.8295454382896423), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-08 21:25:49,872 | 2092374713.py:37 | Aggregated accuracy: 0.7138924869624051 +- 0.08942773415911504\n",
      "DEBUG flower 2022-04-08 21:25:49,872 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:25:57,496 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:25:57,520 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:00,405 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:26:00,405 | 2092374713.py:15 | round-107-EVALUATION\n",
      "INFO flower 2022-04-08 21:26:00,408 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6398467421531677), (5, 0.7984032034873962), (7, 0.6086956262588501), (9, 0.6437246799468994), (11, 0.7165354490280151), (13, 0.6900826692581177), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:26:00,408 | 2092374713.py:37 | Aggregated accuracy: 0.7124964594841003 +- 0.08721624543460998\n",
      "DEBUG flower 2022-04-08 21:26:00,409 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:07,892 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:26:07,916 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:10,973 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:26:10,974 | 2092374713.py:15 | round-108-EVALUATION\n",
      "INFO flower 2022-04-08 21:26:10,976 | 2092374713.py:31 | [(1, 0.6561264991760254), (3, 0.6283524632453918), (5, 0.7924151420593262), (7, 0.6086956262588501), (9, 0.6518218517303467), (11, 0.7165354490280151), (13, 0.6983470916748047), (15, 0.7915058135986328), (17, 0.5992063283920288), (19, 0.8257575631141663), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:26:10,977 | 2092374713.py:37 | Aggregated accuracy: 0.711007681759921 +- 0.08673311097716492\n",
      "DEBUG flower 2022-04-08 21:26:10,977 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:18,441 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:26:18,464 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:21,467 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:26:21,467 | 2092374713.py:15 | round-109-EVALUATION\n",
      "INFO flower 2022-04-08 21:26:21,470 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.7944111824035645), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.7953668236732483), (17, 0.5992063283920288), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:26:21,471 | 2092374713.py:37 | Aggregated accuracy: 0.7132600437511097 +- 0.08615346264652327\n",
      "DEBUG flower 2022-04-08 21:26:21,472 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:28,977 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:26:29,000 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:31,926 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:26:31,926 | 2092374713.py:15 | round-110-EVALUATION\n",
      "INFO flower 2022-04-08 21:26:31,929 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6283524632453918), (5, 0.7944111824035645), (7, 0.6047430634498596), (9, 0.6558704376220703), (11, 0.7283464670181274), (13, 0.6900826692581177), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.8295454382896423), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-08 21:26:31,929 | 2092374713.py:37 | Aggregated accuracy: 0.7140579277818854 +- 0.08940214461888729\n",
      "DEBUG flower 2022-04-08 21:26:31,930 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:39,497 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:26:39,519 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:42,460 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:26:42,461 | 2092374713.py:15 | round-111-EVALUATION\n",
      "INFO flower 2022-04-08 21:26:42,463 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6398467421531677), (5, 0.7904191613197327), (7, 0.6086956262588501), (9, 0.659919023513794), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.7876448035240173), (17, 0.5952380895614624), (19, 0.8295454382896423), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:26:42,463 | 2092374713.py:37 | Aggregated accuracy: 0.7144023288380016 +- 0.08551061434157675\n",
      "DEBUG flower 2022-04-08 21:26:42,464 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:49,959 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:26:49,982 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:26:53,106 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:26:53,106 | 2092374713.py:15 | round-112-EVALUATION\n",
      "INFO flower 2022-04-08 21:26:53,109 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.802395224571228), (7, 0.6166008114814758), (9, 0.6396760940551758), (11, 0.7362204790115356), (13, 0.6818181872367859), (15, 0.7799227833747864), (17, 0.5714285969734192), (19, 0.8333333134651184), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:26:53,109 | 2092374713.py:37 | Aggregated accuracy: 0.7105933752926913 +- 0.08767339784345923\n",
      "DEBUG flower 2022-04-08 21:26:53,110 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:00,722 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:27:00,744 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:03,883 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:27:03,883 | 2092374713.py:15 | round-113-EVALUATION\n",
      "INFO flower 2022-04-08 21:27:03,886 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.7984032034873962), (7, 0.6126482486724854), (9, 0.647773265838623), (11, 0.7362204790115356), (13, 0.6900826692581177), (15, 0.7876448035240173), (17, 0.591269850730896), (19, 0.8295454382896423), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:27:03,886 | 2092374713.py:37 | Aggregated accuracy: 0.7139388160272078 +- 0.08570694572773446\n",
      "DEBUG flower 2022-04-08 21:27:03,887 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:11,400 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:27:11,422 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:14,557 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:27:14,558 | 2092374713.py:15 | round-114-EVALUATION\n",
      "INFO flower 2022-04-08 21:27:14,560 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6245210766792297), (5, 0.7904191613197327), (7, 0.6007905006408691), (9, 0.6720647811889648), (11, 0.7244094610214233), (13, 0.702479362487793), (15, 0.7953668236732483), (17, 0.6071428656578064), (19, 0.8257575631141663), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-08 21:27:14,560 | 2092374713.py:37 | Aggregated accuracy: 0.715967985716733 +- 0.08657956166606223\n",
      "DEBUG flower 2022-04-08 21:27:14,561 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:22,019 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:27:22,042 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:24,948 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:27:24,948 | 2092374713.py:15 | round-115-EVALUATION\n",
      "INFO flower 2022-04-08 21:27:24,951 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6245210766792297), (5, 0.7864271402359009), (7, 0.6126482486724854), (9, 0.6639676094055176), (11, 0.7244094610214233), (13, 0.702479362487793), (15, 0.7953668236732483), (17, 0.60317462682724), (19, 0.8181818127632141), (21, 0.8691983222961426)]\n",
      "INFO flower 2022-04-08 21:27:24,952 | 2092374713.py:37 | Aggregated accuracy: 0.7156646576794711 +- 0.08626107077889124\n",
      "DEBUG flower 2022-04-08 21:27:24,952 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:32,531 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:27:32,554 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:35,493 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:27:35,494 | 2092374713.py:15 | round-116-EVALUATION\n",
      "INFO flower 2022-04-08 21:27:35,496 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6245210766792297), (5, 0.7824351191520691), (7, 0.6126482486724854), (9, 0.6639676094055176), (11, 0.7244094610214233), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.60317462682724), (19, 0.8181818127632141), (21, 0.8649789094924927)]\n",
      "INFO flower 2022-04-08 21:27:35,497 | 2092374713.py:37 | Aggregated accuracy: 0.713848514990373 +- 0.08535531331588202\n",
      "DEBUG flower 2022-04-08 21:27:35,497 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:42,869 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:27:42,892 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:45,936 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:27:45,936 | 2092374713.py:15 | round-117-EVALUATION\n",
      "INFO flower 2022-04-08 21:27:45,939 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.802395224571228), (7, 0.6363636255264282), (9, 0.6437246799468994), (11, 0.7401574850082397), (13, 0.6818181872367859), (15, 0.7760617733001709), (17, 0.567460298538208), (19, 0.8295454382896423), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:27:45,939 | 2092374713.py:37 | Aggregated accuracy: 0.7124434330246665 +- 0.0861319285904278\n",
      "DEBUG flower 2022-04-08 21:27:45,940 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:53,366 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:27:53,388 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:27:56,488 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:27:56,489 | 2092374713.py:15 | round-118-EVALUATION\n",
      "INFO flower 2022-04-08 21:27:56,491 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6398467421531677), (5, 0.7984032034873962), (7, 0.6086956262588501), (9, 0.6518218517303467), (11, 0.7244094610214233), (13, 0.702479362487793), (15, 0.7876448035240173), (17, 0.5873016119003296), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:27:56,492 | 2092374713.py:37 | Aggregated accuracy: 0.7140126065774397 +- 0.08638243652498681\n",
      "DEBUG flower 2022-04-08 21:27:56,492 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:03,953 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:28:03,975 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:06,872 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:28:06,872 | 2092374713.py:15 | round-119-EVALUATION\n",
      "INFO flower 2022-04-08 21:28:06,875 | 2092374713.py:31 | [(1, 0.6679841876029968), (3, 0.6283524632453918), (5, 0.7844311594963074), (7, 0.6047430634498596), (9, 0.6680161952972412), (11, 0.7204724550247192), (13, 0.702479362487793), (15, 0.7953668236732483), (17, 0.5952380895614624), (19, 0.8181818127632141), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:28:06,875 | 2092374713.py:37 | Aggregated accuracy: 0.7128914269534025 +- 0.08555841636874127\n",
      "DEBUG flower 2022-04-08 21:28:06,876 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:14,632 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:28:14,655 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:17,516 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:28:17,517 | 2092374713.py:15 | round-120-EVALUATION\n",
      "INFO flower 2022-04-08 21:28:17,519 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6283524632453918), (5, 0.7904191613197327), (7, 0.6245059370994568), (9, 0.6558704376220703), (11, 0.7283464670181274), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.5833333134651184), (19, 0.8219696879386902), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:28:17,519 | 2092374713.py:37 | Aggregated accuracy: 0.7141144980083812 +- 0.08619607889603503\n",
      "DEBUG flower 2022-04-08 21:28:17,520 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:24,979 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:28:25,002 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:28,055 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:28:28,056 | 2092374713.py:15 | round-121-EVALUATION\n",
      "INFO flower 2022-04-08 21:28:28,059 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6360152959823608), (5, 0.796407163143158), (7, 0.6324110627174377), (9, 0.6437246799468994), (11, 0.7322834730148315), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.5753968358039856), (19, 0.8219696879386902), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:28:28,059 | 2092374713.py:37 | Aggregated accuracy: 0.7141985405575145 +- 0.08594158717332309\n",
      "DEBUG flower 2022-04-08 21:28:28,060 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:35,601 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:28:35,624 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:38,553 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:28:38,554 | 2092374713.py:15 | round-122-EVALUATION\n",
      "INFO flower 2022-04-08 21:28:38,556 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6245210766792297), (5, 0.7924151420593262), (7, 0.6245059370994568), (9, 0.647773265838623), (11, 0.7322834730148315), (13, 0.702479362487793), (15, 0.7876448035240173), (17, 0.5753968358039856), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:28:38,557 | 2092374713.py:37 | Aggregated accuracy: 0.7127778096632524 +- 0.0876054551575537\n",
      "DEBUG flower 2022-04-08 21:28:38,557 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:46,252 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:28:46,275 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:49,178 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:28:49,179 | 2092374713.py:15 | round-123-EVALUATION\n",
      "INFO flower 2022-04-08 21:28:49,181 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6360152959823608), (5, 0.7904191613197327), (7, 0.6245059370994568), (9, 0.6518218517303467), (11, 0.7362204790115356), (13, 0.702479362487793), (15, 0.7876448035240173), (17, 0.5753968358039856), (19, 0.8219696879386902), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:28:49,182 | 2092374713.py:37 | Aggregated accuracy: 0.71367854421789 +- 0.08535997009546761\n",
      "DEBUG flower 2022-04-08 21:28:49,183 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:56,727 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:28:56,751 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:28:59,908 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:28:59,909 | 2092374713.py:15 | round-124-EVALUATION\n",
      "INFO flower 2022-04-08 21:28:59,911 | 2092374713.py:31 | [(1, 0.6600790619850159), (3, 0.6321839094161987), (5, 0.7924151420593262), (7, 0.6205533742904663), (9, 0.6761133670806885), (11, 0.7283464670181274), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.5833333134651184), (19, 0.8181818127632141), (21, 0.8565400838851929)]\n",
      "INFO flower 2022-04-08 21:28:59,912 | 2092374713.py:37 | Aggregated accuracy: 0.7147028825499795 +- 0.08554823998381668\n",
      "DEBUG flower 2022-04-08 21:28:59,913 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:07,474 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:29:07,497 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:10,535 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:29:10,535 | 2092374713.py:15 | round-125-EVALUATION\n",
      "INFO flower 2022-04-08 21:29:10,538 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6283524632453918), (5, 0.7944111824035645), (7, 0.6205533742904663), (9, 0.6720647811889648), (11, 0.7244094610214233), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:29:10,538 | 2092374713.py:37 | Aggregated accuracy: 0.7137601213021711 +- 0.08489178730309277\n",
      "DEBUG flower 2022-04-08 21:29:10,539 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:18,028 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:29:18,052 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:20,945 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:29:20,945 | 2092374713.py:15 | round-126-EVALUATION\n",
      "INFO flower 2022-04-08 21:29:20,948 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.7924151420593262), (7, 0.6245059370994568), (9, 0.6558704376220703), (11, 0.7244094610214233), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.5714285969734192), (19, 0.8181818127632141), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:29:20,949 | 2092374713.py:37 | Aggregated accuracy: 0.7120925892483104 +- 0.08600854753718049\n",
      "DEBUG flower 2022-04-08 21:29:20,949 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:28,636 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:29:28,661 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:31,474 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:29:31,475 | 2092374713.py:15 | round-127-EVALUATION\n",
      "INFO flower 2022-04-08 21:29:31,477 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.7944111824035645), (7, 0.6166008114814758), (9, 0.6558704376220703), (11, 0.7283464670181274), (13, 0.6983470916748047), (15, 0.7876448035240173), (17, 0.5714285969734192), (19, 0.8295454382896423), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:29:31,478 | 2092374713.py:37 | Aggregated accuracy: 0.7125790281729265 +- 0.08790003880443477\n",
      "DEBUG flower 2022-04-08 21:29:31,479 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:39,430 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:29:39,452 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:42,482 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:29:42,482 | 2092374713.py:15 | round-128-EVALUATION\n",
      "INFO flower 2022-04-08 21:29:42,485 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.7864271402359009), (7, 0.6245059370994568), (9, 0.659919023513794), (11, 0.7204724550247192), (13, 0.702479362487793), (15, 0.7837837934494019), (17, 0.5753968358039856), (19, 0.8219696879386902), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:29:42,485 | 2092374713.py:37 | Aggregated accuracy: 0.7115614685145292 +- 0.08446260200215575\n",
      "DEBUG flower 2022-04-08 21:29:42,486 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:49,546 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:29:49,568 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:52,465 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:29:52,466 | 2092374713.py:15 | round-129-EVALUATION\n",
      "INFO flower 2022-04-08 21:29:52,468 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.7864271402359009), (7, 0.6205533742904663), (9, 0.659919023513794), (11, 0.712598443031311), (13, 0.6983470916748047), (15, 0.7915058135986328), (17, 0.579365074634552), (19, 0.8219696879386902), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:29:52,469 | 2092374713.py:37 | Aggregated accuracy: 0.7119163220578973 +- 0.08537191710044136\n",
      "DEBUG flower 2022-04-08 21:29:52,469 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:29:59,077 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:29:59,101 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:01,685 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:01,685 | 2092374713.py:15 | round-130-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:01,688 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6436781883239746), (5, 0.7924151420593262), (7, 0.6245059370994568), (9, 0.6356275081634521), (11, 0.7322834730148315), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.567460298538208), (19, 0.8333333134651184), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:30:01,688 | 2092374713.py:37 | Aggregated accuracy: 0.7114869898015802 +- 0.08729474724390052\n",
      "DEBUG flower 2022-04-08 21:30:01,690 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:08,338 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:30:08,361 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:11,092 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:11,092 | 2092374713.py:15 | round-131-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:11,094 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7864271402359009), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7165354490280151), (13, 0.702479362487793), (15, 0.7876448035240173), (17, 0.5753968358039856), (19, 0.8295454382896423), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:30:11,095 | 2092374713.py:37 | Aggregated accuracy: 0.711500655521046 +- 0.08768453547727664\n",
      "DEBUG flower 2022-04-08 21:30:11,095 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:17,627 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:30:17,649 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:20,316 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:20,316 | 2092374713.py:15 | round-132-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:20,318 | 2092374713.py:31 | [(1, 0.6640316247940063), (3, 0.6091954112052917), (5, 0.7784430980682373), (7, 0.6007905006408691), (9, 0.6842105388641357), (11, 0.6968504190444946), (13, 0.7066115736961365), (15, 0.799227774143219), (17, 0.5992063283920288), (19, 0.810606062412262), (21, 0.8607594966888428)]\n",
      "INFO flower 2022-04-08 21:30:20,319 | 2092374713.py:37 | Aggregated accuracy: 0.7099938934499567 +- 0.08677146412749039\n",
      "DEBUG flower 2022-04-08 21:30:20,320 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:26,841 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:30:26,863 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:29,389 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:29,390 | 2092374713.py:15 | round-133-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:29,392 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6206896305084229), (5, 0.7864271402359009), (7, 0.6047430634498596), (9, 0.6558704376220703), (11, 0.7086614370346069), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.579365074634552), (19, 0.8257575631141663), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:30:29,393 | 2092374713.py:37 | Aggregated accuracy: 0.7097874608906832 +- 0.08850142144135312\n",
      "DEBUG flower 2022-04-08 21:30:29,393 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:36,056 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:30:36,078 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:38,588 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:38,589 | 2092374713.py:15 | round-134-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:38,591 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6168582439422607), (5, 0.7864271402359009), (7, 0.6007905006408691), (9, 0.6680161952972412), (11, 0.7086614370346069), (13, 0.702479362487793), (15, 0.7953668236732483), (17, 0.5833333134651184), (19, 0.8181818127632141), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:30:38,592 | 2092374713.py:37 | Aggregated accuracy: 0.709464127367193 +- 0.0871424055231024\n",
      "DEBUG flower 2022-04-08 21:30:38,592 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:45,090 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:30:45,112 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:47,774 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:47,774 | 2092374713.py:15 | round-135-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:47,777 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6206896305084229), (5, 0.7864271402359009), (7, 0.6007905006408691), (9, 0.659919023513794), (11, 0.7047244310379028), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.5753968358039856), (19, 0.8257575631141663), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:30:47,777 | 2092374713.py:37 | Aggregated accuracy: 0.7087182077494535 +- 0.0893910320804663\n",
      "DEBUG flower 2022-04-08 21:30:47,778 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:54,231 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:30:54,254 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:30:56,774 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:30:56,774 | 2092374713.py:15 | round-136-EVALUATION\n",
      "INFO flower 2022-04-08 21:30:56,777 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6475095748901367), (5, 0.7904191613197327), (7, 0.6245059370994568), (9, 0.6396760940551758), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.7799227833747864), (17, 0.5753968358039856), (19, 0.8333333134651184), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:30:56,777 | 2092374713.py:37 | Aggregated accuracy: 0.7121267427097667 +- 0.08588356486084349\n",
      "DEBUG flower 2022-04-08 21:30:56,777 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:03,438 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:03,461 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:05,974 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:31:05,974 | 2092374713.py:15 | round-137-EVALUATION\n",
      "INFO flower 2022-04-08 21:31:05,976 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.7804391384124756), (7, 0.6007905006408691), (9, 0.647773265838623), (11, 0.712598443031311), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.5714285969734192), (19, 0.8295454382896423), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:31:05,977 | 2092374713.py:37 | Aggregated accuracy: 0.7072712995789268 +- 0.08782633561241453\n",
      "DEBUG flower 2022-04-08 21:31:05,978 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:12,456 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:12,478 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:15,141 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:31:15,142 | 2092374713.py:15 | round-138-EVALUATION\n",
      "INFO flower 2022-04-08 21:31:15,144 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6245210766792297), (5, 0.7804391384124756), (7, 0.6007905006408691), (9, 0.6518218517303467), (11, 0.6968504190444946), (13, 0.6983470916748047), (15, 0.7915058135986328), (17, 0.5753968358039856), (19, 0.8219696879386902), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:31:15,145 | 2092374713.py:37 | Aggregated accuracy: 0.7059666351838545 +- 0.08803067678673833\n",
      "DEBUG flower 2022-04-08 21:31:15,145 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:21,647 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:21,670 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:24,167 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:31:24,168 | 2092374713.py:15 | round-139-EVALUATION\n",
      "INFO flower 2022-04-08 21:31:24,170 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6283524632453918), (5, 0.7844311594963074), (7, 0.6007905006408691), (9, 0.6437246799468994), (11, 0.7007874250411987), (13, 0.6942148804664612), (15, 0.7953668236732483), (17, 0.567460298538208), (19, 0.8295454382896423), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:31:24,171 | 2092374713.py:37 | Aggregated accuracy: 0.7054750377481634 +- 0.08969966163444745\n",
      "DEBUG flower 2022-04-08 21:31:24,171 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:30,827 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:30,851 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:33,366 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:31:33,367 | 2092374713.py:15 | round-140-EVALUATION\n",
      "INFO flower 2022-04-08 21:31:33,369 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.7824351191520691), (7, 0.5968379378318787), (9, 0.6518218517303467), (11, 0.7047244310379028), (13, 0.6983470916748047), (15, 0.7953668236732483), (17, 0.567460298538208), (19, 0.8257575631141663), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:31:33,370 | 2092374713.py:37 | Aggregated accuracy: 0.7064078883691267 +- 0.08867457643172362\n",
      "DEBUG flower 2022-04-08 21:31:33,370 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:39,880 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:39,902 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:42,565 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:31:42,565 | 2092374713.py:15 | round-141-EVALUATION\n",
      "INFO flower 2022-04-08 21:31:42,568 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6321839094161987), (5, 0.7844311594963074), (7, 0.6126482486724854), (9, 0.6558704376220703), (11, 0.7007874250411987), (13, 0.6983470916748047), (15, 0.7953668236732483), (17, 0.567460298538208), (19, 0.8219696879386902), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:31:42,568 | 2092374713.py:37 | Aggregated accuracy: 0.7073088559237394 +- 0.085909822560576\n",
      "DEBUG flower 2022-04-08 21:31:42,569 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:49,082 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:49,104 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:51,611 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:31:51,612 | 2092374713.py:15 | round-142-EVALUATION\n",
      "INFO flower 2022-04-08 21:31:51,615 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6245210766792297), (5, 0.7864271402359009), (7, 0.6086956262588501), (9, 0.6518218517303467), (11, 0.7086614370346069), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:31:51,615 | 2092374713.py:37 | Aggregated accuracy: 0.7079198577187278 +- 0.08594090939693948\n",
      "DEBUG flower 2022-04-08 21:31:51,615 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:31:58,288 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:31:58,311 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:00,841 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:00,842 | 2092374713.py:15 | round-143-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:00,844 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7844311594963074), (7, 0.6047430634498596), (9, 0.6356275081634521), (11, 0.7165354490280151), (13, 0.6942148804664612), (15, 0.7876448035240173), (17, 0.5714285969734192), (19, 0.8295454382896423), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:32:00,845 | 2092374713.py:37 | Aggregated accuracy: 0.7075929045677185 +- 0.08766860855143915\n",
      "DEBUG flower 2022-04-08 21:32:00,845 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:07,518 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:32:07,541 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:10,266 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:10,267 | 2092374713.py:15 | round-144-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:10,269 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6436781883239746), (5, 0.7824351191520691), (7, 0.6007905006408691), (9, 0.6639676094055176), (11, 0.7007874250411987), (13, 0.7066115736961365), (15, 0.7953668236732483), (17, 0.5833333134651184), (19, 0.8219696879386902), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:32:10,270 | 2092374713.py:37 | Aggregated accuracy: 0.7107919454574585 +- 0.08460476105246041\n",
      "DEBUG flower 2022-04-08 21:32:10,270 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:16,779 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:32:16,802 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:19,475 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:19,475 | 2092374713.py:15 | round-145-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:19,478 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.7844311594963074), (7, 0.6007905006408691), (9, 0.6558704376220703), (11, 0.7007874250411987), (13, 0.7066115736961365), (15, 0.7915058135986328), (17, 0.5833333134651184), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:32:19,478 | 2092374713.py:37 | Aggregated accuracy: 0.7073705196380615 +- 0.08423348330577086\n",
      "DEBUG flower 2022-04-08 21:32:19,478 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:25,979 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:32:26,002 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:28,547 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:28,548 | 2092374713.py:15 | round-146-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:28,550 | 2092374713.py:31 | [(1, 0.6719367504119873), (3, 0.6321839094161987), (5, 0.7844311594963074), (7, 0.6086956262588501), (9, 0.6558704376220703), (11, 0.7086614370346069), (13, 0.6983470916748047), (15, 0.7953668236732483), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:32:28,551 | 2092374713.py:37 | Aggregated accuracy: 0.7088110880418257 +- 0.08546099745923635\n",
      "DEBUG flower 2022-04-08 21:32:28,551 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:35,205 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:32:35,228 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:37,749 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:37,750 | 2092374713.py:15 | round-147-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:37,752 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6360152959823608), (5, 0.7864271402359009), (7, 0.6047430634498596), (9, 0.6518218517303467), (11, 0.7086614370346069), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:32:37,753 | 2092374713.py:37 | Aggregated accuracy: 0.7082461389628324 +- 0.08554401458541126\n",
      "DEBUG flower 2022-04-08 21:32:37,753 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:44,271 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:32:44,293 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:46,977 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:46,977 | 2092374713.py:15 | round-148-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:46,979 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6126482486724854), (9, 0.6275303363800049), (11, 0.712598443031311), (13, 0.6859503984451294), (15, 0.7915058135986328), (17, 0.5753968358039856), (19, 0.8257575631141663), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:32:46,980 | 2092374713.py:37 | Aggregated accuracy: 0.707594708962874 +- 0.088451825824652\n",
      "DEBUG flower 2022-04-08 21:32:46,980 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:53,482 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:32:53,504 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:32:56,009 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:32:56,010 | 2092374713.py:15 | round-149-EVALUATION\n",
      "INFO flower 2022-04-08 21:32:56,012 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6360152959823608), (5, 0.7864271402359009), (7, 0.6086956262588501), (9, 0.6558704376220703), (11, 0.7204724550247192), (13, 0.6983470916748047), (15, 0.7953668236732483), (17, 0.5833333134651184), (19, 0.8181818127632141), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:32:56,013 | 2092374713.py:37 | Aggregated accuracy: 0.7119018164548007 +- 0.08590008335389183\n",
      "DEBUG flower 2022-04-08 21:32:56,013 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:02,678 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:02,700 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:05,216 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:33:05,217 | 2092374713.py:15 | round-150-EVALUATION\n",
      "INFO flower 2022-04-08 21:33:05,219 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7884231805801392), (7, 0.6205533742904663), (9, 0.6518218517303467), (11, 0.7244094610214233), (13, 0.6900826692581177), (15, 0.7876448035240173), (17, 0.5714285969734192), (19, 0.8219696879386902), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:33:05,220 | 2092374713.py:37 | Aggregated accuracy: 0.710516788742759 +- 0.08450297715867162\n",
      "DEBUG flower 2022-04-08 21:33:05,220 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:11,710 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:11,732 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:14,391 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:33:14,391 | 2092374713.py:15 | round-151-EVALUATION\n",
      "INFO flower 2022-04-08 21:33:14,394 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6283524632453918), (5, 0.7884231805801392), (7, 0.6166008114814758), (9, 0.659919023513794), (11, 0.7244094610214233), (13, 0.6983470916748047), (15, 0.8030887842178345), (17, 0.591269850730896), (19, 0.814393937587738), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:33:14,394 | 2092374713.py:37 | Aggregated accuracy: 0.7139104171232744 +- 0.0849076624960446\n",
      "DEBUG flower 2022-04-08 21:33:14,395 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:20,917 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:20,940 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:23,456 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:33:23,457 | 2092374713.py:15 | round-152-EVALUATION\n",
      "INFO flower 2022-04-08 21:33:23,459 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6047430634498596), (9, 0.647773265838623), (11, 0.7244094610214233), (13, 0.7066115736961365), (15, 0.8030887842178345), (17, 0.5873016119003296), (19, 0.8181818127632141), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:33:23,459 | 2092374713.py:37 | Aggregated accuracy: 0.7138820507309653 +- 0.08731287959208228\n",
      "DEBUG flower 2022-04-08 21:33:23,460 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:30,108 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:30,130 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:32,640 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:33:32,640 | 2092374713.py:15 | round-153-EVALUATION\n",
      "INFO flower 2022-04-08 21:33:32,642 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7904191613197327), (7, 0.6086956262588501), (9, 0.6518218517303467), (11, 0.7165354490280151), (13, 0.7066115736961365), (15, 0.799227774143219), (17, 0.5873016119003296), (19, 0.8181818127632141), (21, 0.852320671081543)]\n",
      "INFO flower 2022-04-08 21:33:32,643 | 2092374713.py:37 | Aggregated accuracy: 0.7137094681913202 +- 0.08571798718155627\n",
      "DEBUG flower 2022-04-08 21:33:32,643 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:39,151 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:39,174 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:41,850 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:33:41,850 | 2092374713.py:15 | round-154-EVALUATION\n",
      "INFO flower 2022-04-08 21:33:41,853 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6126482486724854), (9, 0.6315789222717285), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.7876448035240173), (17, 0.579365074634552), (19, 0.8257575631141663), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:33:41,853 | 2092374713.py:37 | Aggregated accuracy: 0.7090560631318525 +- 0.08658056346072521\n",
      "DEBUG flower 2022-04-08 21:33:41,854 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:48,372 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:48,394 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:50,913 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:33:50,914 | 2092374713.py:15 | round-155-EVALUATION\n",
      "INFO flower 2022-04-08 21:33:50,916 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6283524632453918), (5, 0.7904191613197327), (7, 0.6086956262588501), (9, 0.6396760940551758), (11, 0.7165354490280151), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:33:50,917 | 2092374713.py:37 | Aggregated accuracy: 0.7089940526268699 +- 0.08669464567744227\n",
      "DEBUG flower 2022-04-08 21:33:50,917 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:33:57,415 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:33:57,438 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:00,116 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:00,116 | 2092374713.py:15 | round-156-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:00,119 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6283524632453918), (5, 0.7884231805801392), (7, 0.6047430634498596), (9, 0.647773265838623), (11, 0.7165354490280151), (13, 0.702479362487793), (15, 0.799227774143219), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:34:00,119 | 2092374713.py:37 | Aggregated accuracy: 0.7098913788795471 +- 0.08708986578700217\n",
      "DEBUG flower 2022-04-08 21:34:00,120 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:06,781 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:34:06,804 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:09,812 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:09,813 | 2092374713.py:15 | round-157-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:09,815 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.7884231805801392), (7, 0.6047430634498596), (9, 0.6558704376220703), (11, 0.712598443031311), (13, 0.7066115736961365), (15, 0.799227774143219), (17, 0.5952380895614624), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:34:09,816 | 2092374713.py:37 | Aggregated accuracy: 0.7116693800145929 +- 0.0829473051169228\n",
      "DEBUG flower 2022-04-08 21:34:09,817 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:16,373 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:34:16,396 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:18,925 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:18,925 | 2092374713.py:15 | round-158-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:18,928 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.7904191613197327), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7244094610214233), (13, 0.6942148804664612), (15, 0.799227774143219), (17, 0.579365074634552), (19, 0.8219696879386902), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:34:18,928 | 2092374713.py:37 | Aggregated accuracy: 0.710705740885301 +- 0.08654730768690239\n",
      "DEBUG flower 2022-04-08 21:34:18,928 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:25,453 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:34:25,475 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:28,158 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:28,158 | 2092374713.py:15 | round-159-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:28,161 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.796407163143158), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7204724550247192), (13, 0.6900826692581177), (15, 0.7953668236732483), (17, 0.5873016119003296), (19, 0.8181818127632141), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:34:28,161 | 2092374713.py:37 | Aggregated accuracy: 0.7105426950888201 +- 0.0852413523135895\n",
      "DEBUG flower 2022-04-08 21:34:28,162 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:34,657 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:34:34,679 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:37,235 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:37,235 | 2092374713.py:15 | round-160-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:37,238 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.8003991842269897), (7, 0.6086956262588501), (9, 0.6356275081634521), (11, 0.7244094610214233), (13, 0.6859503984451294), (15, 0.7953668236732483), (17, 0.567460298538208), (19, 0.8219696879386902), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:34:37,238 | 2092374713.py:37 | Aggregated accuracy: 0.7082537466829474 +- 0.08810466694688678\n",
      "DEBUG flower 2022-04-08 21:34:37,239 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:43,911 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:34:43,933 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:46,468 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:46,468 | 2092374713.py:15 | round-161-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:46,471 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6475095748901367), (5, 0.8003991842269897), (7, 0.6166008114814758), (9, 0.623481810092926), (11, 0.7244094610214233), (13, 0.6776859760284424), (15, 0.7915058135986328), (17, 0.5436508059501648), (19, 0.8333333134651184), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:34:46,471 | 2092374713.py:37 | Aggregated accuracy: 0.706331112168052 +- 0.09269729107915735\n",
      "DEBUG flower 2022-04-08 21:34:46,472 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:52,965 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:34:52,988 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:34:55,668 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:34:55,669 | 2092374713.py:15 | round-162-EVALUATION\n",
      "INFO flower 2022-04-08 21:34:55,671 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7944111824035645), (7, 0.6086956262588501), (9, 0.6437246799468994), (11, 0.7244094610214233), (13, 0.6942148804664612), (15, 0.8030887842178345), (17, 0.5634920597076416), (19, 0.8257575631141663), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:34:55,672 | 2092374713.py:37 | Aggregated accuracy: 0.7102659886533563 +- 0.08910316860668199\n",
      "DEBUG flower 2022-04-08 21:34:55,672 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:02,178 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:02,201 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:04,877 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:04,877 | 2092374713.py:15 | round-163-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:04,880 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6245210766792297), (5, 0.7864271402359009), (7, 0.5968379378318787), (9, 0.6558704376220703), (11, 0.712598443031311), (13, 0.7148760557174683), (15, 0.7953668236732483), (17, 0.6190476417541504), (19, 0.8068181872367859), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:35:04,881 | 2092374713.py:37 | Aggregated accuracy: 0.7120122638615695 +- 0.08140296924994389\n",
      "DEBUG flower 2022-04-08 21:35:04,882 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:11,378 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:11,400 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:13,929 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:13,930 | 2092374713.py:15 | round-164-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:13,932 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6283524632453918), (5, 0.796407163143158), (7, 0.6047430634498596), (9, 0.647773265838623), (11, 0.7165354490280151), (13, 0.7148760557174683), (15, 0.8030887842178345), (17, 0.60317462682724), (19, 0.814393937587738), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:35:13,933 | 2092374713.py:37 | Aggregated accuracy: 0.7131724140860818 +- 0.08420248896778093\n",
      "DEBUG flower 2022-04-08 21:35:13,933 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:20,444 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:20,466 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:23,139 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:23,139 | 2092374713.py:15 | round-165-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:23,142 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.799227774143219), (17, 0.5753968358039856), (19, 0.8257575631141663), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:35:23,142 | 2092374713.py:37 | Aggregated accuracy: 0.7108611952174794 +- 0.08736168212048569\n",
      "DEBUG flower 2022-04-08 21:35:23,143 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:29,664 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:29,686 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:32,206 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:32,207 | 2092374713.py:15 | round-166-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:32,210 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7904191613197327), (7, 0.6166008114814758), (9, 0.6396760940551758), (11, 0.7244094610214233), (13, 0.6900826692581177), (15, 0.799227774143219), (17, 0.5634920597076416), (19, 0.8219696879386902), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:35:32,210 | 2092374713.py:37 | Aggregated accuracy: 0.7091826688159596 +- 0.08752319822046661\n",
      "DEBUG flower 2022-04-08 21:35:32,211 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:38,873 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:38,896 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:41,420 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:41,420 | 2092374713.py:15 | round-167-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:41,422 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6126482486724854), (9, 0.647773265838623), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.80694979429245), (17, 0.5753968358039856), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:35:41,423 | 2092374713.py:37 | Aggregated accuracy: 0.7108502388000488 +- 0.08625145851694284\n",
      "DEBUG flower 2022-04-08 21:35:41,424 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:47,955 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:47,977 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:50,643 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:50,643 | 2092374713.py:15 | round-168-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:50,645 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.796407163143158), (7, 0.6086956262588501), (9, 0.6437246799468994), (11, 0.712598443031311), (13, 0.71074378490448), (15, 0.80694979429245), (17, 0.579365074634552), (19, 0.814393937587738), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:35:50,646 | 2092374713.py:37 | Aggregated accuracy: 0.7109406644647772 +- 0.08643568916619836\n",
      "DEBUG flower 2022-04-08 21:35:50,647 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:57,175 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:35:57,196 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:35:59,724 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:35:59,725 | 2092374713.py:15 | round-169-EVALUATION\n",
      "INFO flower 2022-04-08 21:35:59,727 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6245210766792297), (5, 0.7904191613197327), (7, 0.6047430634498596), (9, 0.6356275081634521), (11, 0.712598443031311), (13, 0.71074378490448), (15, 0.7953668236732483), (17, 0.591269850730896), (19, 0.814393937587738), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:35:59,728 | 2092374713.py:37 | Aggregated accuracy: 0.7090170871127736 +- 0.0854853267166504\n",
      "DEBUG flower 2022-04-08 21:35:59,728 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:06,498 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:36:06,521 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:09,096 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:36:09,097 | 2092374713.py:15 | round-170-EVALUATION\n",
      "INFO flower 2022-04-08 21:36:09,099 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7944111824035645), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7244094610214233), (13, 0.6942148804664612), (15, 0.799227774143219), (17, 0.5634920597076416), (19, 0.8181818127632141), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:36:09,100 | 2092374713.py:37 | Aggregated accuracy: 0.7099779194051569 +- 0.08815771138072097\n",
      "DEBUG flower 2022-04-08 21:36:09,100 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:15,672 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:36:15,694 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:18,368 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:36:18,368 | 2092374713.py:15 | round-171-EVALUATION\n",
      "INFO flower 2022-04-08 21:36:18,370 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6436781883239746), (5, 0.8003991842269897), (7, 0.6086956262588501), (9, 0.6194332242012024), (11, 0.7283464670181274), (13, 0.6818181872367859), (15, 0.7876448035240173), (17, 0.5396825671195984), (19, 0.8257575631141663), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:36:18,371 | 2092374713.py:37 | Aggregated accuracy: 0.7056665095415983 +- 0.09307735231055371\n",
      "DEBUG flower 2022-04-08 21:36:18,372 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:24,904 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:36:24,926 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:27,465 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:36:27,466 | 2092374713.py:15 | round-172-EVALUATION\n",
      "INFO flower 2022-04-08 21:36:27,468 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6283524632453918), (5, 0.7944111824035645), (7, 0.6047430634498596), (9, 0.647773265838623), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.567460298538208), (19, 0.814393937587738), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:36:27,468 | 2092374713.py:37 | Aggregated accuracy: 0.7079137346961282 +- 0.08829003919276128\n",
      "DEBUG flower 2022-04-08 21:36:27,469 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:34,124 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:36:34,145 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:36,671 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:36:36,671 | 2092374713.py:15 | round-173-EVALUATION\n",
      "INFO flower 2022-04-08 21:36:36,673 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6321839094161987), (5, 0.7884231805801392), (7, 0.6047430634498596), (9, 0.6518218517303467), (11, 0.7204724550247192), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.5634920597076416), (19, 0.8181818127632141), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:36:36,674 | 2092374713.py:37 | Aggregated accuracy: 0.7084370743144642 +- 0.08756377351418383\n",
      "DEBUG flower 2022-04-08 21:36:36,674 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:43,204 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:36:43,227 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:45,902 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:36:45,903 | 2092374713.py:15 | round-174-EVALUATION\n",
      "INFO flower 2022-04-08 21:36:45,905 | 2092374713.py:31 | [(1, 0.6758893132209778), (3, 0.6283524632453918), (5, 0.7864271402359009), (7, 0.6047430634498596), (9, 0.6396760940551758), (11, 0.712598443031311), (13, 0.7066115736961365), (15, 0.7953668236732483), (17, 0.579365074634552), (19, 0.8181818127632141), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:36:45,906 | 2092374713.py:37 | Aggregated accuracy: 0.708664823662151 +- 0.08781297561973482\n",
      "DEBUG flower 2022-04-08 21:36:45,906 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:52,431 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:36:52,454 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:36:54,988 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:36:54,989 | 2092374713.py:15 | round-175-EVALUATION\n",
      "INFO flower 2022-04-08 21:36:54,992 | 2092374713.py:31 | [(1, 0.6916996240615845), (3, 0.6283524632453918), (5, 0.7884231805801392), (7, 0.6086956262588501), (9, 0.6396760940551758), (11, 0.7165354490280151), (13, 0.6942148804664612), (15, 0.8030887842178345), (17, 0.5555555820465088), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:36:54,992 | 2092374713.py:37 | Aggregated accuracy: 0.7072605924172835 +- 0.08970995545558348\n",
      "DEBUG flower 2022-04-08 21:36:54,993 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:01,651 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:01,673 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:04,196 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:04,196 | 2092374713.py:15 | round-176-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:04,199 | 2092374713.py:31 | [(1, 0.687747061252594), (3, 0.6398467421531677), (5, 0.7924151420593262), (7, 0.6126482486724854), (9, 0.6356275081634521), (11, 0.7204724550247192), (13, 0.6942148804664612), (15, 0.8030887842178345), (17, 0.5555555820465088), (19, 0.8181818127632141), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:37:04,199 | 2092374713.py:37 | Aggregated accuracy: 0.7082747112620961 +- 0.08865701352778323\n",
      "DEBUG flower 2022-04-08 21:37:04,199 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:10,793 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:10,815 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:13,336 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:13,337 | 2092374713.py:15 | round-177-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:13,339 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6513410210609436), (5, 0.7984032034873962), (7, 0.6166008114814758), (9, 0.6194332242012024), (11, 0.7283464670181274), (13, 0.6818181872367859), (15, 0.7915058135986328), (17, 0.5317460298538208), (19, 0.8257575631141663), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:37:13,340 | 2092374713.py:37 | Aggregated accuracy: 0.706529828635129 +- 0.09337052655672395\n",
      "DEBUG flower 2022-04-08 21:37:13,340 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:19,977 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:20,000 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:22,528 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:22,528 | 2092374713.py:15 | round-178-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:22,531 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6245210766792297), (5, 0.7884231805801392), (7, 0.5968379378318787), (9, 0.6437246799468994), (11, 0.7047244310379028), (13, 0.702479362487793), (15, 0.7915058135986328), (17, 0.567460298538208), (19, 0.8181818127632141), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:37:22,531 | 2092374713.py:37 | Aggregated accuracy: 0.7040640603412281 +- 0.08718594395618356\n",
      "DEBUG flower 2022-04-08 21:37:22,532 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:29,085 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:29,107 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:31,784 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:31,784 | 2092374713.py:15 | round-179-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:31,787 | 2092374713.py:31 | [(1, 0.6837944388389587), (3, 0.6283524632453918), (5, 0.7844311594963074), (7, 0.5968379378318787), (9, 0.6315789222717285), (11, 0.7047244310379028), (13, 0.7066115736961365), (15, 0.7915058135986328), (17, 0.5714285969734192), (19, 0.8219696879386902), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:37:31,787 | 2092374713.py:37 | Aggregated accuracy: 0.7047689665447582 +- 0.0877312448215188\n",
      "DEBUG flower 2022-04-08 21:37:31,788 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:38,331 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:38,353 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:40,872 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:40,872 | 2092374713.py:15 | round-180-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:40,875 | 2092374713.py:31 | [(1, 0.687747061252594), (3, 0.6398467421531677), (5, 0.7844311594963074), (7, 0.5968379378318787), (9, 0.6356275081634521), (11, 0.7086614370346069), (13, 0.6983470916748047), (15, 0.7876448035240173), (17, 0.5595238208770752), (19, 0.8257575631141663), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:37:40,875 | 2092374713.py:37 | Aggregated accuracy: 0.7050589756532148 +- 0.08838417877779862\n",
      "DEBUG flower 2022-04-08 21:37:40,876 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:47,423 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:47,445 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:50,113 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:50,113 | 2092374713.py:15 | round-181-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:50,116 | 2092374713.py:31 | [(1, 0.687747061252594), (3, 0.6360152959823608), (5, 0.7924151420593262), (7, 0.6007905006408691), (9, 0.6396760940551758), (11, 0.7086614370346069), (13, 0.702479362487793), (15, 0.8030887842178345), (17, 0.5714285969734192), (19, 0.814393937587738), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:37:50,116 | 2092374713.py:37 | Aggregated accuracy: 0.7083762938326056 +- 0.08747171172471359\n",
      "DEBUG flower 2022-04-08 21:37:50,117 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:56,665 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:37:56,686 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:37:59,212 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:37:59,213 | 2092374713.py:15 | round-182-EVALUATION\n",
      "INFO flower 2022-04-08 21:37:59,215 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6206896305084229), (5, 0.7884231805801392), (7, 0.5928853750228882), (9, 0.6518218517303467), (11, 0.7047244310379028), (13, 0.7066115736961365), (15, 0.7915058135986328), (17, 0.5833333134651184), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:37:59,215 | 2092374713.py:37 | Aggregated accuracy: 0.7066783525727012 +- 0.08643517349538755\n",
      "DEBUG flower 2022-04-08 21:37:59,216 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:06,010 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:38:06,032 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:08,611 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:38:08,612 | 2092374713.py:15 | round-183-EVALUATION\n",
      "INFO flower 2022-04-08 21:38:08,614 | 2092374713.py:31 | [(1, 0.6916996240615845), (3, 0.6398467421531677), (5, 0.7944111824035645), (7, 0.6086956262588501), (9, 0.6396760940551758), (11, 0.7165354490280151), (13, 0.6900826692581177), (15, 0.7915058135986328), (17, 0.567460298538208), (19, 0.8219696879386902), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:38:08,615 | 2092374713.py:37 | Aggregated accuracy: 0.7088478370146318 +- 0.08699445918808757\n",
      "DEBUG flower 2022-04-08 21:38:08,615 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:15,158 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:38:15,180 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:17,862 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:38:17,862 | 2092374713.py:15 | round-184-EVALUATION\n",
      "INFO flower 2022-04-08 21:38:17,865 | 2092374713.py:31 | [(1, 0.687747061252594), (3, 0.6283524632453918), (5, 0.796407163143158), (7, 0.5889328122138977), (9, 0.647773265838623), (11, 0.7047244310379028), (13, 0.6942148804664612), (15, 0.7953668236732483), (17, 0.579365074634552), (19, 0.810606062412262), (21, 0.8270041942596436)]\n",
      "INFO flower 2022-04-08 21:38:17,865 | 2092374713.py:37 | Aggregated accuracy: 0.7054994756525214 +- 0.08601050732701021\n",
      "DEBUG flower 2022-04-08 21:38:17,866 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:24,399 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:38:24,421 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:26,943 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:38:26,944 | 2092374713.py:15 | round-185-EVALUATION\n",
      "INFO flower 2022-04-08 21:38:26,946 | 2092374713.py:31 | [(1, 0.6837944388389587), (3, 0.6321839094161987), (5, 0.7864271402359009), (7, 0.5928853750228882), (9, 0.647773265838623), (11, 0.7086614370346069), (13, 0.6983470916748047), (15, 0.7953668236732483), (17, 0.5753968358039856), (19, 0.814393937587738), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:38:26,947 | 2092374713.py:37 | Aggregated accuracy: 0.7068084261634133 +- 0.08702803439278349\n",
      "DEBUG flower 2022-04-08 21:38:26,948 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:33,459 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:38:33,481 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:36,151 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:38:36,151 | 2092374713.py:15 | round-186-EVALUATION\n",
      "INFO flower 2022-04-08 21:38:36,154 | 2092374713.py:31 | [(1, 0.6916996240615845), (3, 0.6283524632453918), (5, 0.7844311594963074), (7, 0.6126482486724854), (9, 0.6356275081634521), (11, 0.712598443031311), (13, 0.6983470916748047), (15, 0.8030887842178345), (17, 0.567460298538208), (19, 0.8181818127632141), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:38:36,154 | 2092374713.py:37 | Aggregated accuracy: 0.7083725333213806 +- 0.08798863506248643\n",
      "DEBUG flower 2022-04-08 21:38:36,155 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:42,657 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:38:42,679 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:45,205 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:38:45,205 | 2092374713.py:15 | round-187-EVALUATION\n",
      "INFO flower 2022-04-08 21:38:45,208 | 2092374713.py:31 | [(1, 0.6798418760299683), (3, 0.6398467421531677), (5, 0.7824351191520691), (7, 0.6047430634498596), (9, 0.647773265838623), (11, 0.712598443031311), (13, 0.702479362487793), (15, 0.799227774143219), (17, 0.5753968358039856), (19, 0.8219696879386902), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:38:45,208 | 2092374713.py:37 | Aggregated accuracy: 0.7100176377729936 +- 0.08667258305012357\n",
      "DEBUG flower 2022-04-08 21:38:45,209 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:51,895 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:38:51,918 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:38:54,438 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:38:54,438 | 2092374713.py:15 | round-188-EVALUATION\n",
      "INFO flower 2022-04-08 21:38:54,441 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6436781883239746), (5, 0.7904191613197327), (7, 0.6126482486724854), (9, 0.6356275081634521), (11, 0.7165354490280151), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.5634920597076416), (19, 0.814393937587738), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:38:54,441 | 2092374713.py:37 | Aggregated accuracy: 0.7085100412368774 +- 0.0858590795661309\n",
      "DEBUG flower 2022-04-08 21:38:54,442 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:00,956 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:00,979 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:03,672 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:03,672 | 2092374713.py:15 | round-189-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:03,674 | 2092374713.py:31 | [(1, 0.687747061252594), (3, 0.6475095748901367), (5, 0.7844311594963074), (7, 0.6086956262588501), (9, 0.6437246799468994), (11, 0.712598443031311), (13, 0.702479362487793), (15, 0.799227774143219), (17, 0.5634920597076416), (19, 0.8181818127632141), (21, 0.8312236070632935)]\n",
      "INFO flower 2022-04-08 21:39:03,675 | 2092374713.py:37 | Aggregated accuracy: 0.7090282873673872 +- 0.08553192035133897\n",
      "DEBUG flower 2022-04-08 21:39:03,675 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:10,208 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:10,230 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:12,755 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:12,756 | 2092374713.py:15 | round-190-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:12,758 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6436781883239746), (5, 0.7904191613197327), (7, 0.6047430634498596), (9, 0.6396760940551758), (11, 0.7165354490280151), (13, 0.6900826692581177), (15, 0.7876448035240173), (17, 0.567460298538208), (19, 0.810606062412262), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:39:12,759 | 2092374713.py:37 | Aggregated accuracy: 0.7078327644955028 +- 0.08568659213578972\n",
      "DEBUG flower 2022-04-08 21:39:12,759 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:19,284 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:19,305 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:22,013 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:22,013 | 2092374713.py:15 | round-191-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:22,015 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6398467421531677), (5, 0.7904191613197327), (7, 0.6086956262588501), (9, 0.6437246799468994), (11, 0.712598443031311), (13, 0.6900826692581177), (15, 0.799227774143219), (17, 0.5714285969734192), (19, 0.814393937587738), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:39:22,016 | 2092374713.py:37 | Aggregated accuracy: 0.710379188710993 +- 0.08727445035177067\n",
      "DEBUG flower 2022-04-08 21:39:22,016 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:28,550 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:28,573 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:31,091 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:31,091 | 2092374713.py:15 | round-192-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:31,094 | 2092374713.py:31 | [(1, 0.6916996240615845), (3, 0.6283524632453918), (5, 0.7864271402359009), (7, 0.6086956262588501), (9, 0.647773265838623), (11, 0.7047244310379028), (13, 0.6983470916748047), (15, 0.799227774143219), (17, 0.567460298538208), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:39:31,094 | 2092374713.py:37 | Aggregated accuracy: 0.7086155793883584 +- 0.08791857223020318\n",
      "DEBUG flower 2022-04-08 21:39:31,094 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:37,827 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:37,850 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:40,373 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:40,373 | 2092374713.py:15 | round-193-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:40,376 | 2092374713.py:31 | [(1, 0.6916996240615845), (3, 0.6360152959823608), (5, 0.7844311594963074), (7, 0.6007905006408691), (9, 0.6396760940551758), (11, 0.7007874250411987), (13, 0.6942148804664612), (15, 0.7953668236732483), (17, 0.567460298538208), (19, 0.8181818127632141), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:39:40,376 | 2092374713.py:37 | Aggregated accuracy: 0.7062078497626565 +- 0.08765499178012777\n",
      "DEBUG flower 2022-04-08 21:39:40,377 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:46,907 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:46,930 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:49,456 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:49,457 | 2092374713.py:15 | round-194-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:49,459 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6360152959823608), (5, 0.7864271402359009), (7, 0.6086956262588501), (9, 0.6396760940551758), (11, 0.7086614370346069), (13, 0.6983470916748047), (15, 0.7953668236732483), (17, 0.5555555820465088), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:39:49,460 | 2092374713.py:37 | Aggregated accuracy: 0.7070929191329263 +- 0.08808734312176351\n",
      "DEBUG flower 2022-04-08 21:39:49,460 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:56,142 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:39:56,165 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:39:58,682 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:39:58,682 | 2092374713.py:15 | round-195-EVALUATION\n",
      "INFO flower 2022-04-08 21:39:58,685 | 2092374713.py:31 | [(1, 0.687747061252594), (3, 0.6245210766792297), (5, 0.7904191613197327), (7, 0.6007905006408691), (9, 0.6558704376220703), (11, 0.7047244310379028), (13, 0.702479362487793), (15, 0.8030887842178345), (17, 0.5833333134651184), (19, 0.8181818127632141), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:39:58,685 | 2092374713.py:37 | Aggregated accuracy: 0.710841563614932 +- 0.08774324105819431\n",
      "DEBUG flower 2022-04-08 21:39:58,685 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:05,265 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:40:05,287 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:08,022 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:40:08,022 | 2092374713.py:15 | round-196-EVALUATION\n",
      "INFO flower 2022-04-08 21:40:08,025 | 2092374713.py:31 | [(1, 0.6996047496795654), (3, 0.6360152959823608), (5, 0.7904191613197327), (7, 0.6166008114814758), (9, 0.6396760940551758), (11, 0.7086614370346069), (13, 0.6942148804664612), (15, 0.7953668236732483), (17, 0.5555555820465088), (19, 0.8219696879386902), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:40:08,025 | 2092374713.py:37 | Aggregated accuracy: 0.7085025039586154 +- 0.08808979339859138\n",
      "DEBUG flower 2022-04-08 21:40:08,026 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:14,650 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:40:14,673 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:17,213 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:40:17,213 | 2092374713.py:15 | round-197-EVALUATION\n",
      "INFO flower 2022-04-08 21:40:17,215 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6321839094161987), (5, 0.7904191613197327), (7, 0.5968379378318787), (9, 0.6437246799468994), (11, 0.7007874250411987), (13, 0.6942148804664612), (15, 0.7953668236732483), (17, 0.5714285969734192), (19, 0.8181818127632141), (21, 0.8438818454742432)]\n",
      "INFO flower 2022-04-08 21:40:17,216 | 2092374713.py:37 | Aggregated accuracy: 0.7075162963433699 +- 0.08857964159690626\n",
      "DEBUG flower 2022-04-08 21:40:17,216 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:23,749 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:40:23,772 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:26,458 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:40:26,459 | 2092374713.py:15 | round-198-EVALUATION\n",
      "INFO flower 2022-04-08 21:40:26,461 | 2092374713.py:31 | [(1, 0.695652186870575), (3, 0.6360152959823608), (5, 0.796407163143158), (7, 0.6007905006408691), (9, 0.6396760940551758), (11, 0.7086614370346069), (13, 0.6900826692581177), (15, 0.7876448035240173), (17, 0.5714285969734192), (19, 0.8219696879386902), (21, 0.8481012582778931)]\n",
      "INFO flower 2022-04-08 21:40:26,462 | 2092374713.py:37 | Aggregated accuracy: 0.7087663357908075 +- 0.08905546225389144\n",
      "DEBUG flower 2022-04-08 21:40:26,462 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:32,991 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:40:33,013 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:35,532 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:40:35,532 | 2092374713.py:15 | round-199-EVALUATION\n",
      "INFO flower 2022-04-08 21:40:35,535 | 2092374713.py:31 | [(1, 0.6916996240615845), (3, 0.6321839094161987), (5, 0.7864271402359009), (7, 0.6007905006408691), (9, 0.6356275081634521), (11, 0.7047244310379028), (13, 0.6983470916748047), (15, 0.7915058135986328), (17, 0.5714285969734192), (19, 0.8181818127632141), (21, 0.8354430198669434)]\n",
      "INFO flower 2022-04-08 21:40:35,535 | 2092374713.py:37 | Aggregated accuracy: 0.7060326771302656 +- 0.08684589839341561\n",
      "DEBUG flower 2022-04-08 21:40:35,536 | server.py:265 | fit_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:42,232 | server.py:277 | fit_round received 11 results and 0 failures\n",
      "DEBUG flower 2022-04-08 21:40:42,254 | server.py:211 | evaluate_round: strategy sampled 11 clients (out of 11)\n",
      "DEBUG flower 2022-04-08 21:40:44,767 | server.py:223 | evaluate_round received 11 results and 0 failures\n",
      "INFO flower 2022-04-08 21:40:44,767 | 2092374713.py:15 | round-200-EVALUATION\n",
      "INFO flower 2022-04-08 21:40:44,769 | 2092374713.py:31 | [(1, 0.6996047496795654), (3, 0.6321839094161987), (5, 0.7884231805801392), (7, 0.6007905006408691), (9, 0.6396760940551758), (11, 0.7007874250411987), (13, 0.6942148804664612), (15, 0.7915058135986328), (17, 0.567460298538208), (19, 0.814393937587738), (21, 0.8396624326705933)]\n",
      "INFO flower 2022-04-08 21:40:44,770 | 2092374713.py:37 | Aggregated accuracy: 0.7062457474795255 +- 0.08740500023734979\n",
      "INFO flower 2022-04-08 21:40:44,771 | server.py:182 | FL finished in 2011.0446978000002\n",
      "INFO flower 2022-04-08 21:40:44,771 | app.py:149 | app_fit: losses_distributed [(1, 0.6929371859157397), (2, 0.682092111334673), (3, 0.6709824207402443), (4, 0.659623013164206), (5, 0.6482031866291915), (6, 0.6369260459438366), (7, 0.6256981002468168), (8, 0.6152610964937554), (9, 0.6057644787112333), (10, 0.5973655747886214), (11, 0.5900100169495719), (12, 0.5836066487132813), (13, 0.5785177136311419), (14, 0.5740191582177516), (15, 0.5705663533822771), (16, 0.5674889401966793), (17, 0.5650482975289083), (18, 0.5629221859689663), (19, 0.561348320650731), (20, 0.5599029887562511), (21, 0.558913689435731), (22, 0.5581157114818874), (23, 0.5573404399795797), (24, 0.55686109980092), (25, 0.5562436166304136), (26, 0.5560246273712571), (27, 0.5555783491476931), (28, 0.5550020176903759), (29, 0.5543295883241175), (30, 0.5539033296405579), (31, 0.5535269592757104), (32, 0.5531730220446396), (33, 0.5528962149885842), (34, 0.552786089521822), (35, 0.5521044363515724), (36, 0.551552836829134), (37, 0.5512136971165792), (38, 0.5509980354252297), (39, 0.5509207946474174), (40, 0.5500911316590084), (41, 0.5494750955721577), (42, 0.5488999135696134), (43, 0.5488997030013687), (44, 0.5484382428359481), (45, 0.5482853656173187), (46, 0.548449163656932), (47, 0.5483272457769522), (48, 0.5474821744949424), (49, 0.5473063918205826), (50, 0.547118348561491), (51, 0.5471389544865882), (52, 0.5476849496936388), (53, 0.5475969495479137), (54, 0.5475321587469655), (55, 0.5468150351247052), (56, 0.5465471321310856), (57, 0.5473440351606086), (58, 0.5472322222199063), (59, 0.5476760132262299), (60, 0.5479282693006406), (61, 0.5475684410879795), (62, 0.5475587201777019), (63, 0.5482414016020128), (64, 0.5468572995598018), (65, 0.5467703938089851), (66, 0.5469308990616693), (67, 0.5462954029159912), (68, 0.5469875888756637), (69, 0.5470929170360717), (70, 0.5466255165372824), (71, 0.5466223223849003), (72, 0.5462500229108188), (73, 0.5463206881803272), (74, 0.5473205826257264), (75, 0.5467453566837343), (76, 0.5476272043273263), (77, 0.5486919207167554), (78, 0.5475954024396588), (79, 0.5472296532557731), (80, 0.5467671580437671), (81, 0.5475241628518926), (82, 0.5471162645086484), (83, 0.5476374851229804), (84, 0.5488244149608403), (85, 0.5481488304918191), (86, 0.5483185283955541), (87, 0.5477128728332008), (88, 0.5478267864876538), (89, 0.5482119114202575), (90, 0.548494637505408), (91, 0.5493398921855664), (92, 0.5487887851063321), (93, 0.5495671707689467), (94, 0.5507919695098945), (95, 0.550829033957307), (96, 0.5497725053295724), (97, 0.5485828714854978), (98, 0.5488393684905213), (99, 0.5483037115247527), (100, 0.5484750928308567), (101, 0.5479265218277148), (102, 0.5483333597583878), (103, 0.548974682844675), (104, 0.5487024656715986), (105, 0.5498840624316812), (106, 0.5495943842524138), (107, 0.5501976351823943), (108, 0.5503394104394935), (109, 0.5494939726766592), (110, 0.5494356054937134), (111, 0.5505881304185674), (112, 0.5497421933904295), (113, 0.5491488369300671), (114, 0.5500658135657827), (115, 0.5503060706415753), (116, 0.5506134820209211), (117, 0.5490254998660584), (118, 0.5505314163230248), (119, 0.5514868280270855), (120, 0.5504253944083235), (121, 0.5507697691161862), (122, 0.550648533081401), (123, 0.5513342355719631), (124, 0.5517859938737772), (125, 0.5511717584170216), (126, 0.5514364103055576), (127, 0.550866566694536), (128, 0.5511788622141279), (129, 0.5512363461422045), (130, 0.5504460826915422), (131, 0.5514985387722783), (132, 0.553242183790434), (133, 0.5524896119372796), (134, 0.5528770469984312), (135, 0.5528582362516645), (136, 0.550915904572339), (137, 0.551978750868503), (138, 0.5526489434043501), (139, 0.5520218851015815), (140, 0.5531168358435585), (141, 0.5521582487084555), (142, 0.5516048065388869), (143, 0.551882438507058), (144, 0.5532087558967327), (145, 0.5531344016064408), (146, 0.55255694316193), (147, 0.5522366790356638), (148, 0.5524324064533954), (149, 0.5521429899884027), (150, 0.551826957200404), (151, 0.5525489619560602), (152, 0.5535424819282061), (153, 0.5539005094220455), (154, 0.5532611055540557), (155, 0.5542053434772283), (156, 0.5546112177863328), (157, 0.5543661690826965), (158, 0.5542380188696833), (159, 0.5542743168068847), (160, 0.5545157572902121), (161, 0.5546903930138642), (162, 0.5549698537779375), (163, 0.5568587209978839), (164, 0.5562381749314028), (165, 0.554690242888239), (166, 0.5544788555084693), (167, 0.5548430630457232), (168, 0.5555076558011043), (169, 0.555862580225478), (170, 0.5560384373809973), (171, 0.5561332080958105), (172, 0.5572237370821013), (173, 0.5572771506517721), (174, 0.5576039450850031), (175, 0.556845906896383), (176, 0.5573440146513265), (177, 0.5569216960161836), (178, 0.5574787245299933), (179, 0.5586482116985195), (180, 0.5581889061532666), (181, 0.5580597535648213), (182, 0.5591510692713003), (183, 0.5574749951484067), (184, 0.5591258751588905), (185, 0.5590412867136282), (186, 0.5586348495517311), (187, 0.5596792695244692), (188, 0.559682050555343), (189, 0.5604038437864775), (190, 0.5593677699033527), (191, 0.5597136327161956), (192, 0.5600781553122053), (193, 0.5605291848521022), (194, 0.5604633227350536), (195, 0.5600967963247397), (196, 0.5596886222878317), (197, 0.560344412977081), (198, 0.5597256986443427), (199, 0.56064341196823), (200, 0.560504773171422)]\n",
      "INFO flower 2022-04-08 21:40:44,772 | app.py:150 | app_fit: metrics_distributed {}\n",
      "INFO flower 2022-04-08 21:40:44,772 | app.py:151 | app_fit: losses_centralized []\n",
      "INFO flower 2022-04-08 21:40:44,772 | app.py:152 | app_fit: metrics_centralized {}\n"
     ]
    }
   ],
   "source": [
    "# Select the company that will perform the federated training of a common model for all its clients\n",
    "company = 1\n",
    "\n",
    "IDS_COMPANY = {\n",
    "    1: list(range(2,22,2)), # Even\n",
    "    2: list(range(1,22,2)), # Odds\n",
    "}\n",
    "\n",
    "for company in [1, 2]:\n",
    "    CLIENTS_IDS = IDS_COMPANY[company]\n",
    "¡\n",
    "    # Initialize a file for results\n",
    "    header = CLIENTS_IDS\n",
    "    with open(f\"./results/milestone1-company_{company}.csv\", 'w', ) as f:\n",
    "        csv_writer = writer(f)\n",
    "        csv_writer.writerow(header)\n",
    "\n",
    "    # Parameter config for training from the server\n",
    "    def fit_config(rnd: int) -> Dict[str, str]:\n",
    "        config = {\n",
    "            \"round\": str(rnd),\n",
    "            \"epochs\": str(1) #if rnd < 2 else str(2)\n",
    "        }\n",
    "        return config\n",
    "\n",
    "    # Start Flower simulation\n",
    "        # min_fit_clients and min_eval_clients are set to the max clients available as we are in a controled environment\n",
    "    fl.simulation.start_simulation(\n",
    "        client_fn=client_fn,\n",
    "        clients_ids=CLIENTS_IDS,\n",
    "        client_resources={\"num_cpus\": 6},\n",
    "        num_rounds=200,\n",
    "        strategy=SaveModelStrategy(\n",
    "            min_available_clients = len(CLIENTS_IDS),\n",
    "            min_fit_clients = len(CLIENTS_IDS),\n",
    "            min_eval_clients = len(CLIENTS_IDS),\n",
    "            on_fit_config_fn = fit_config,\n",
    "            on_evaluate_config_fn = fit_config,\n",
    "        )\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Results visualization\n",
    "\n",
    "It shows the metrics obtained during the federated process with the progress visualization"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acc máximo empresa 1: 0.723741102218628\n",
      "Acc máximo empresa 2: 0.7167612151666121\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1440x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_e1 = pd.read_csv(f'./results/milestone1-company_1.csv')\n",
    "df_e1[\"mean\"] = df_e1.mean(numeric_only=True, axis=1)\n",
    "\n",
    "df_e2 = pd.read_csv(f'./results/milestone1-company_2.csv')\n",
    "df_e2[\"mean\"] = df_e2.mean(numeric_only=True, axis=1)\n",
    "\n",
    "print(f'Acc max company 1: {df_e1[\"mean\"].max()}')\n",
    "print(f'Acc máx company 2: {df_e2[\"mean\"].max()}')\n",
    "\n",
    "f, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,6))\n",
    "\n",
    "df_e1.plot(ax=ax1, ylim=(0,1))\n",
    "df_e2.plot(ax=ax2, ylim=(0,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "name": "flower.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}