Training in progress, step 5000

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

@@ -33369,3 +33369,43 @@ If your task is similar to the task the model of the checkpoint was trained on,
 [INFO|tokenization_utils_base.py:2157] 2022-12-15 06:16:15,438 >> tokenizer config file saved in ./tokenizer_config.json
 [INFO|tokenization_utils_base.py:2164] 2022-12-15 06:16:15,438 >> Special tokens file saved in ./special_tokens_map.json
 [INFO|tokenization_utils_base.py:2210] 2022-12-15 06:16:15,439 >> added tokens file saved in ./added_tokens.json
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 42%|████▏     | 5000/12000 [21:36:09<18:37:50,  9.58s/it][INFO|trainer.py:2955] 2022-12-15 09:04:17,161 >> ***** Running Evaluation *****
+[INFO|trainer.py:2959] 2022-12-15 09:04:17,161 >>   Num examples: Unknown
+[INFO|trainer.py:2960] 2022-12-15 09:04:17,161 >>   Batch size = 64
+{'eval_loss': 0.12609383463859558, 'eval_wer': 13.262534350177791, 'eval_runtime': 6883.3335, 'eval_samples_per_second': 2.306, 'eval_steps_per_second': 0.036, 'epoch': 0.33}
+{'loss': 0.0891, 'learning_rate': 6.915652173913044e-05, 'epoch': 0.34}
+{'loss': 0.1144, 'learning_rate': 6.872173913043478e-05, 'epoch': 0.34}
+{'loss': 0.096, 'learning_rate': 6.828695652173914e-05, 'epoch': 0.35}
+{'loss': 0.1078, 'learning_rate': 6.785217391304349e-05, 'epoch': 0.35}
+{'loss': 0.0791, 'learning_rate': 6.741739130434783e-05, 'epoch': 0.35}
+{'loss': 0.0946, 'learning_rate': 6.698260869565218e-05, 'epoch': 0.36}
+{'loss': 0.0767, 'learning_rate': 6.654782608695652e-05, 'epoch': 0.36}
+{'loss': 0.0753, 'learning_rate': 6.611304347826088e-05, 'epoch': 0.37}
+{'loss': 0.0857, 'learning_rate': 6.567826086956522e-05, 'epoch': 0.37}
+{'loss': 0.0887, 'learning_rate': 6.524347826086957e-05, 'epoch': 0.38}
+{'loss': 0.0723, 'learning_rate': 6.480869565217391e-05, 'epoch': 0.38}
+{'loss': 0.0952, 'learning_rate': 6.437391304347827e-05, 'epoch': 0.38}
+{'loss': 0.0687, 'learning_rate': 6.393913043478262e-05, 'epoch': 0.39}
+{'loss': 0.0967, 'learning_rate': 6.350434782608696e-05, 'epoch': 0.39}
+{'loss': 0.0804, 'learning_rate': 6.30695652173913e-05, 'epoch': 0.4}
+{'loss': 0.118, 'learning_rate': 6.263478260869565e-05, 'epoch': 0.4}
+{'loss': 0.1065, 'learning_rate': 6.220000000000001e-05, 'epoch': 0.4}
+{'loss': 0.1005, 'learning_rate': 6.176521739130436e-05, 'epoch': 0.41}
+{'loss': 0.1045, 'learning_rate': 6.13304347826087e-05, 'epoch': 0.41}
+{'loss': 0.099, 'learning_rate': 6.0895652173913044e-05, 'epoch': 0.42}
+
+
+
+
+[INFO|trainer_utils.py:689] 2022-12-15 09:04:25,925 >> 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.
+
                                                          
 42%|████▏     | 5000/12000 [23:30:56<18:37:50,  9.58s/it][INFO|trainer.py:2700] 2022-12-15 10:59:04,578 >> Saving model checkpoint to ./checkpoint-5000
+[INFO|configuration_utils.py:447] 2022-12-15 10:59:04,579 >> Configuration saved in ./checkpoint-5000/config.json
+[INFO|modeling_utils.py:1680] 2022-12-15 10:59:05,584 >> Model weights saved in ./checkpoint-5000/pytorch_model.bin
+[INFO|feature_extraction_utils.py:368] 2022-12-15 10:59:05,599 >> Feature extractor saved in ./checkpoint-5000/preprocessor_config.json
+[INFO|tokenization_utils_base.py:2157] 2022-12-15 10:59:05,600 >> tokenizer config file saved in ./checkpoint-5000/tokenizer_config.json
+[INFO|tokenization_utils_base.py:2164] 2022-12-15 10:59:05,600 >> Special tokens file saved in ./checkpoint-5000/special_tokens_map.json
+[INFO|tokenization_utils_base.py:2210] 2022-12-15 10:59:05,600 >> added tokens file saved in ./checkpoint-5000/added_tokens.json
+[INFO|feature_extraction_utils.py:368] 2022-12-15 10:59:10,547 >> Feature extractor saved in ./preprocessor_config.json
+[INFO|tokenization_utils_base.py:2157] 2022-12-15 10:59:10,548 >> tokenizer config file saved in ./tokenizer_config.json
+[INFO|tokenization_utils_base.py:2164] 2022-12-15 10:59:10,548 >> Special tokens file saved in ./special_tokens_map.json
+[INFO|tokenization_utils_base.py:2210] 2022-12-15 10:59:10,549 >> added tokens file saved in ./added_tokens.json