Training in progress, step 4000

nohup.out

@@ -70431,3 +70431,75 @@ If your task is similar to the task the model of the checkpoint was trained on,
 [INFO|modeling_utils.py:1693] 2023-12-29 19:38:54,229 >> Model weights saved in ./checkpoint-3000/pytorch_model.bin
 [INFO|feature_extraction_utils.py:368] 2023-12-29 19:38:54,235 >> Feature extractor saved in ./checkpoint-3000/preprocessor_config.json
 [INFO|feature_extraction_utils.py:368] 2023-12-29 19:38:59,893 >> Feature extractor saved in ./preprocessor_config.json
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+{'loss': 0.0609, 'learning_rate': 4.395555555555556e-06, 'epoch': 3.14}
+{'loss': 0.0455, 'learning_rate': 4.34e-06, 'epoch': 3.14}
+{'loss': 0.0323, 'learning_rate': 4.284444444444445e-06, 'epoch': 3.15}
+{'loss': 0.0298, 'learning_rate': 4.228888888888889e-06, 'epoch': 3.15}
+{'loss': 0.0265, 'learning_rate': 4.173333333333334e-06, 'epoch': 3.16}
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+{'loss': 0.1179, 'learning_rate': 4.006666666666667e-06, 'epoch': 4.01}
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+{'loss': 0.1806, 'learning_rate': 3.895555555555556e-06, 'epoch': 4.02}
+{'loss': 0.2425, 'learning_rate': 3.8400000000000005e-06, 'epoch': 4.03}
+{'loss': 0.1122, 'learning_rate': 3.784444444444445e-06, 'epoch': 4.03}
+{'loss': 0.0986, 'learning_rate': 3.728888888888889e-06, 'epoch': 4.04}
+{'loss': 0.0942, 'learning_rate': 3.673333333333334e-06, 'epoch': 4.04}
+{'loss': 0.1099, 'learning_rate': 3.617777777777778e-06, 'epoch': 4.05}
+{'loss': 0.1332, 'learning_rate': 3.5622222222222224e-06, 'epoch': 4.05}
+{'loss': 0.1368, 'learning_rate': 3.5066666666666673e-06, 'epoch': 4.06}
+{'loss': 0.164, 'learning_rate': 3.4511111111111113e-06, 'epoch': 4.06}
+{'loss': 0.174, 'learning_rate': 3.3955555555555558e-06, 'epoch': 4.07}
+{'loss': 0.1675, 'learning_rate': 3.3400000000000006e-06, 'epoch': 4.07}
+{'loss': 0.0996, 'learning_rate': 3.2844444444444447e-06, 'epoch': 4.08}
+{'loss': 0.0795, 'learning_rate': 3.228888888888889e-06, 'epoch': 4.08}
+{'loss': 0.0683, 'learning_rate': 3.173333333333334e-06, 'epoch': 4.09}
+{'loss': 0.0635, 'learning_rate': 3.117777777777778e-06, 'epoch': 4.09}
+{'loss': 0.0751, 'learning_rate': 3.0622222222222225e-06, 'epoch': 4.1}
+{'loss': 0.0712, 'learning_rate': 3.0066666666666674e-06, 'epoch': 4.1}
+{'loss': 0.0703, 'learning_rate': 2.9511111111111114e-06, 'epoch': 4.11}
+{'loss': 0.1152, 'learning_rate': 2.895555555555556e-06, 'epoch': 4.11}
+{'loss': 0.1039, 'learning_rate': 2.84e-06, 'epoch': 4.12}
+{'loss': 0.0863, 'learning_rate': 2.784444444444445e-06, 'epoch': 4.12}
+{'loss': 0.0882, 'learning_rate': 2.7288888888888893e-06, 'epoch': 4.13}
+{'loss': 0.0677, 'learning_rate': 2.6733333333333333e-06, 'epoch': 4.13}
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+{'loss': 0.0246, 'learning_rate': 2.5066666666666667e-06, 'epoch': 4.15}
+{'loss': 0.0231, 'learning_rate': 2.451111111111111e-06, 'epoch': 4.15}
+
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 80%|████████  | 4000/5000 [5:57:51<1:06:24,  3.98s/it][INFO|trainer.py:2955] 2023-12-29 20:46:59,900 >> ***** Running Evaluation *****
+[INFO|trainer.py:2959] 2023-12-29 20:46:59,900 >>   Num examples: Unknown
+[INFO|trainer.py:2960] 2023-12-29 20:46:59,900 >>   Batch size = 16
+{'loss': 0.0442, 'learning_rate': 2.3955555555555556e-06, 'epoch': 5.0}
+{'loss': 0.063, 'learning_rate': 2.3400000000000005e-06, 'epoch': 5.01}
+{'loss': 0.0548, 'learning_rate': 2.2844444444444445e-06, 'epoch': 5.01}
+{'loss': 0.0633, 'learning_rate': 2.228888888888889e-06, 'epoch': 5.02}
+
+
+
+
+[INFO|trainer_utils.py:689] 2023-12-29 20:47:03,984 >> The following columns in the evaluation set don't have a corresponding argument in `WhisperForConditionalGeneration.forward` and have been ignored: input_length. If input_length are not expected by `WhisperForConditionalGeneration.forward`,  you can safely ignore this message.
+
                                                       
 80%|████████  | 4000/5000 [6:26:21<1:06:24,  3.98s/it][INFO|trainer.py:2700] 2023-12-29 21:15:30,320 >> Saving model checkpoint to ./checkpoint-4000
+[INFO|configuration_utils.py:447] 2023-12-29 21:15:30,320 >> Configuration saved in ./checkpoint-4000/config.json
+[INFO|modeling_utils.py:1693] 2023-12-29 21:15:31,502 >> Model weights saved in ./checkpoint-4000/pytorch_model.bin
+[INFO|feature_extraction_utils.py:368] 2023-12-29 21:15:31,509 >> Feature extractor saved in ./checkpoint-4000/preprocessor_config.json
+[INFO|feature_extraction_utils.py:368] 2023-12-29 21:15:37,221 >> Feature extractor saved in ./preprocessor_config.json

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