Training in progress, step 10000

pytorch_model.bin

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runs/Dec14_11-27-46_129-213-88-66/events.out.tfevents.1671017287.129-213-88-66.335324.0

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train_run_1.log

@@ -33619,3 +33619,43 @@ If your task is similar to the task the model of the checkpoint was trained on,
 [INFO|tokenization_utils_base.py:2157] 2022-12-16 05:47:34,749 >> tokenizer config file saved in ./tokenizer_config.json
 [INFO|tokenization_utils_base.py:2164] 2022-12-16 05:47:34,749 >> Special tokens file saved in ./special_tokens_map.json
 [INFO|tokenization_utils_base.py:2210] 2022-12-16 05:47:34,749 >> added tokens file saved in ./added_tokens.json
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 83%|████████▎ | 10000/12000 [45:06:14<5:26:48,  9.80s/it][INFO|trainer.py:2955] 2022-12-16 08:34:22,671 >> ***** Running Evaluation *****
+[INFO|trainer.py:2959] 2022-12-16 08:34:22,671 >>   Num examples: Unknown
+[INFO|trainer.py:2960] 2022-12-16 08:34:22,671 >>   Batch size = 64
+{'eval_loss': 0.0796533077955246, 'eval_wer': 7.924892890800092, 'eval_runtime': 6857.0536, 'eval_samples_per_second': 2.315, 'eval_steps_per_second': 0.036, 'epoch': 1.3}
+{'loss': 0.031, 'learning_rate': 2.5678260869565218e-05, 'epoch': 1.3}
+{'loss': 0.0355, 'learning_rate': 2.524347826086957e-05, 'epoch': 1.31}
+{'loss': 0.0278, 'learning_rate': 2.4808695652173914e-05, 'epoch': 1.31}
+{'loss': 0.0295, 'learning_rate': 2.437391304347826e-05, 'epoch': 1.31}
+{'loss': 0.0323, 'learning_rate': 2.3939130434782613e-05, 'epoch': 1.32}
+{'loss': 0.0313, 'learning_rate': 2.3504347826086957e-05, 'epoch': 1.32}
+{'loss': 0.029, 'learning_rate': 2.3069565217391305e-05, 'epoch': 1.33}
+{'loss': 0.0327, 'learning_rate': 2.2634782608695653e-05, 'epoch': 1.33}
+{'loss': 0.0246, 'learning_rate': 2.22e-05, 'epoch': 1.34}
+{'loss': 0.0333, 'learning_rate': 2.176521739130435e-05, 'epoch': 1.34}
+{'loss': 0.031, 'learning_rate': 2.1330434782608697e-05, 'epoch': 1.34}
+{'loss': 0.0471, 'learning_rate': 2.0895652173913044e-05, 'epoch': 1.35}
+{'loss': 0.0725, 'learning_rate': 2.0460869565217392e-05, 'epoch': 1.35}
+{'loss': 0.0773, 'learning_rate': 2.002608695652174e-05, 'epoch': 1.36}
+{'loss': 0.0616, 'learning_rate': 1.9591304347826088e-05, 'epoch': 1.36}
+{'loss': 0.0698, 'learning_rate': 1.9156521739130436e-05, 'epoch': 1.36}
+{'loss': 0.0631, 'learning_rate': 1.8721739130434784e-05, 'epoch': 1.37}
+{'loss': 0.0592, 'learning_rate': 1.828695652173913e-05, 'epoch': 1.37}
+{'loss': 0.0583, 'learning_rate': 1.785217391304348e-05, 'epoch': 1.38}
+{'loss': 0.0604, 'learning_rate': 1.7417391304347827e-05, 'epoch': 1.38}
+
+
+
+
+[INFO|trainer_utils.py:689] 2022-12-16 08:34:31,094 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: labels_length, input_length, labels_truncated. If labels_length, input_length, labels_truncated are not expected by `WhisperForConditionalGeneration.forward`,  you can safely ignore this message.
+
                                                          
 83%|████████▎ | 10000/12000 [47:00:11<5:26:48,  9.80s/it][INFO|trainer.py:2700] 2022-12-16 10:28:19,090 >> Saving model checkpoint to ./checkpoint-10000
+[INFO|configuration_utils.py:447] 2022-12-16 10:28:19,091 >> Configuration saved in ./checkpoint-10000/config.json
+[INFO|modeling_utils.py:1680] 2022-12-16 10:28:19,937 >> Model weights saved in ./checkpoint-10000/pytorch_model.bin
+[INFO|feature_extraction_utils.py:368] 2022-12-16 10:28:19,951 >> Feature extractor saved in ./checkpoint-10000/preprocessor_config.json
+[INFO|tokenization_utils_base.py:2157] 2022-12-16 10:28:19,952 >> tokenizer config file saved in ./checkpoint-10000/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2164] 2022-12-16 10:28:19,952 >> Special tokens file saved in ./checkpoint-10000/special_tokens_map.json
+[INFO|tokenization_utils_base.py:2210] 2022-12-16 10:28:19,952 >> added tokens file saved in ./checkpoint-10000/added_tokens.json
+[INFO|feature_extraction_utils.py:368] 2022-12-16 10:28:24,748 >> Feature extractor saved in ./preprocessor_config.json
+[INFO|tokenization_utils_base.py:2157] 2022-12-16 10:28:24,749 >> tokenizer config file saved in ./tokenizer_config.json
+[INFO|tokenization_utils_base.py:2164] 2022-12-16 10:28:24,749 >> Special tokens file saved in ./special_tokens_map.json
+[INFO|tokenization_utils_base.py:2210] 2022-12-16 10:28:24,750 >> added tokens file saved in ./added_tokens.json