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Training in progress, step 1000
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0%| | 500/499680 [20:05<135:25:31, 1.02it/s]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
***** Running Evaluation *****
Num examples = 40740
Batch size = 12
Configuration saved in ./checkpoint-500/config.json
{'eval_loss': 2.797088623046875, 'eval_wer': 1.0, 'eval_runtime': 2782.5245, 'eval_samples_per_second': 14.641, 'eval_steps_per_second': 1.22, 'epoch': 0.04}
Model weights saved in ./checkpoint-500/pytorch_model.bin
Feature extractor saved in ./checkpoint-500/preprocessor_config.json
Feature extractor saved in ./preprocessor_config.json
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0%|▏ | 1000/499680 [1:28:03<139:02:50, 1.00s/it]The following columns in the evaluation set don't have a corresponding argument in `Wav2Vec2ForCTC.forward` and have been ignored: input_length. If input_length are not expected by `Wav2Vec2ForCTC.forward`, you can safely ignore this message.
***** Running Evaluation *****
Num examples = 40740
Batch size = 12
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Configuration saved in ./checkpoint-1000/config.json
{'eval_loss': 0.5766342878341675, 'eval_wer': 0.5700615809978635, 'eval_runtime': 2721.0829, 'eval_samples_per_second': 14.972, 'eval_steps_per_second': 1.248, 'epoch': 0.08}
Model weights saved in ./checkpoint-1000/pytorch_model.bin
Feature extractor saved in ./checkpoint-1000/preprocessor_config.json
Feature extractor saved in ./preprocessor_config.json
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