AttributeError: 'CTCTrainer' object has no attribute 'scaler'

[sneha117]

Error while trying the regression model

C:\Users\XTEND\anaconda3\envs\ftorch_gpu\python.exe "C:/Program Files/JetBrains/PyCharm Community Edition 2022.3.2/plugins/python-ce/helpers/pydev/pydevd.py" --multiprocess --qt-support=auto --client 127.0.0.1 --port 63293 --file C:\Users\XTEND\PycharmProjects\Regression_Wav2vec\regression_model_train.py
Connected to pydev debugger (build 223.8617.48)
Dataset({
features: ['name', 'path', 'emotion'],
num_rows: 6925
})
Dataset({
features: ['name', 'path', 'emotion'],
num_rows: 1732
})
A regression problem with 3 items: [0, 1, 2]
C:\Users\XTEND\anaconda3\envs\ftorch_gpu\lib\site-packages\transformers\configuration_utils.py:380: UserWarning: Passing gradient_checkpointing to a config initialization is deprecated and will be removed in v5 Transformers. Using model.gradient_checkpointing_enable() instead, or if you are using the Trainer API, pass gradient_checkpointing=True in your TrainingArguments.
warnings.warn(
regression
Ignored unknown kwarg option normalize
Ignored unknown kwarg option normalize
Ignored unknown kwarg option normalize
Ignored unknown kwarg option normalize
The target sampling rate: 16000
Map: 100%|██████████| 100/100 [00:01<00:00, 60.78 examples/s]
Map: 100%|██████████| 100/100 [00:01<00:00, 56.42 examples/s]
Some weights of Wav2Vec2ForSpeechClassification were not initialized from the model checkpoint at lighteternal/wav2vec2-large-xlsr-53-greek and are newly initialized: ['classifier.out_proj.weight', 'classifier.out_proj.bias', 'classifier.dense.bias', 'classifier.dense.weight', 'wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original0', 'wav2vec2.encoder.pos_conv_embed.conv.parametrizations.weight.original1']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
0%| | 0/60 [00:00<?, ?it/s]C:\Users\XTEND\anaconda3\envs\ftorch_gpu\lib\site-packages\torch\amp\autocast_mode.py:250: UserWarning: User provided device_type of 'cuda', but CUDA is not available. Disabling
warnings.warn(
C:\Users\XTEND\anaconda3\envs\ftorch_gpu\lib\site-packages\torch\utils\checkpoint.py:429: UserWarning: torch.utils.checkpoint: please pass in use_reentrant=True or use_reentrant=False explicitly. The default value of use_reentrant will be updated to be False in the future. To maintain current behavior, pass use_reentrant=True. It is recommended that you use use_reentrant=False. Refer to docs for more details on the differences between the two variants.
warnings.warn(
Traceback (most recent call last):
File "C:\Users\XTEND\anaconda3\envs\ftorch_gpu\lib\contextlib.py", line 153, in exit
self.gen.throw(typ, value, traceback)
File "C:\Users\XTEND\anaconda3\envs\ftorch_gpu\lib\site-packages\accelerate\accelerator.py", line 988, in accumulate
yield
File "C:\Users\XTEND\anaconda3\envs\ftorch_gpu\lib\site-packages\transformers\trainer.py", line 1892, in _inner_training_loop
tr_loss_step = self.training_step(model, inputs)
File "C:\Users\XTEND\PycharmProjects\Regression_Wav2vec\regression_model_train.py", line 456, in training_step
self.scaler.scale(loss).backward()
AttributeError: 'CTCTrainer' object has no attribute 'scaler'
python-BaseException
0%| | 0/60 [00:18<?, ?it/s]

Process finished with exit code -1073741510 (0xC000013A: interrupted by Ctrl+C)

[Kshitijpawar]

trainer = CTCTrainer(
    model=model,
    data_collator=data_collator,
    args=training_args,
    compute_metrics=compute_metrics,
    train_dataset=train_dataset,
    eval_dataset=eval_dataset,
    tokenizer=processor.feature_extractor,
)

In the above code replace CTCTrainer with PyTorch trainer class Trainer. This tutorial is outdated due to newer versions of acclerate and transformers.