ValueError: The following model_kwargs are not used by the model: ['encoder_outputs'] while training the model on Cordv2

[deepanshudashora]

Epoch 0:   0%|                                                                                                                                                                                           | 0/793 [00:00<?, ?it/s]/root/miniconda3/envs/donut/lib/python3.7/site-packages/torch/optim/lr_scheduler.py:136: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate
  "https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate", UserWarning)
Epoch 2: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 793/793 [09:23<00:00,  1.41it/s, loss=0.364, v_num=ment]/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/connectors/data_connector.py:241: PossibleUserWarning: The dataloader, val_dataloader 0, does not have many workers which may be a bottleneck. Consider increasing the value of the `num_workers` argument` (try 12 which is the number of cpus on this machine) in the `DataLoader` init to improve performance.
  category=PossibleUserWarning,
                                                                                                                                                                                                                                Traceback (most recent call last):                                                                                                                                                                        | 0/100 [00:00<?, ?it/s]
  File "train.py", line 149, in <module>
    train(config)
  File "train.py", line 133, in train
    trainer.fit(model_module, data_module)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 697, in fit
    self._fit_impl, model, train_dataloaders, val_dataloaders, datamodule, ckpt_path
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 648, in _call_and_handle_interrupt
    return self.strategy.launcher.launch(trainer_fn, *args, trainer=self, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/strategies/launchers/subprocess_script.py", line 93, in launch
    return function(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 735, in _fit_impl
    results = self._run(model, ckpt_path=self.ckpt_path)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1166, in _run
    results = self._run_stage()
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1252, in _run_stage
    return self._run_train()
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1283, in _run_train
    self.fit_loop.run()
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
    self.advance(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/fit_loop.py", line 271, in advance
    self._outputs = self.epoch_loop.run(self._data_fetcher)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 201, in run
    self.on_advance_end()
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 241, in on_advance_end
    self._run_validation()
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/training_epoch_loop.py", line 299, in _run_validation
    self.val_loop.run()
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
    self.advance(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/dataloader/evaluation_loop.py", line 155, in advance
    dl_outputs = self.epoch_loop.run(self._data_fetcher, dl_max_batches, kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/loop.py", line 200, in run
    self.advance(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 143, in advance
    output = self._evaluation_step(**kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/loops/epoch/evaluation_epoch_loop.py", line 240, in _evaluation_step
    output = self.trainer._call_strategy_hook(hook_name, *kwargs.values())
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/trainer/trainer.py", line 1704, in _call_strategy_hook
    output = fn(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/strategies/ddp.py", line 358, in validation_step
    return self.model(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 1008, in forward
    output = self._run_ddp_forward(*inputs, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/torch/nn/parallel/distributed.py", line 969, in _run_ddp_forward
    return module_to_run(*inputs[0], **kwargs[0])
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/pytorch_lightning/overrides/base.py", line 90, in forward
    return self.module.validation_step(*inputs, **kwargs)
  File "/root/deepanshu/donut/lightning_module.py", line 72, in validation_step
    return_attentions=False,
  File "/root/deepanshu/donut/donut/model.py", line 477, in inference
    output_attentions=return_attentions,
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/transformers/generation_utils.py", line 1146, in generate
    self._validate_model_kwargs(model_kwargs.copy())
  File "/root/miniconda3/envs/donut/lib/python3.7/site-packages/transformers/generation_utils.py", line 862, in _validate_model_kwargs
    f"The following `model_kwargs` are not used by the model: {unused_model_args} (note: typos in the"
ValueError: The following `model_kwargs` are not used by the model: ['encoder_outputs'] (note: typos in the generate arguments will also show up in this list)
Epoch 2: 100%|██████████| 793/793 [09:27<00:00,  1.40it/s, loss=0.364, v_num=ment]         

[atharvjairath]

same!

[SamSamhuns]

Change "transformers>=4.11.3" to "transformers==4.21.1" inside setup.py. The new version of the transformers library is causing this issue.

    ),
    python_requires=">=3.7",
    install_requires=[
-      "transformers>=4.11.3",
+      "transformers==4.21.1",
        "timm",
        "datasets[vision]",
        "pytorch-lightning>=1.6.4",

[atharvjairath]

Thanks @SamSamhuns! It worked

[SamSamhuns]

PR created to support new transformers version #56