Training in progress, step 5000

log

@@ -33544,3 +33544,96 @@ If your task is similar to the task the model of the checkpoint was trained on,
 [INFO|modeling_utils.py:1680] 2022-12-15 09:34:42,921 >> Model weights saved in ./checkpoint-4000/pytorch_model.bin
 [INFO|feature_extraction_utils.py:368] 2022-12-15 09:34:42,936 >> Feature extractor saved in ./checkpoint-4000/preprocessor_config.json
 [INFO|feature_extraction_utils.py:368] 2022-12-15 09:34:46,763 >> Feature extractor saved in ./preprocessor_config.json
+/home/ubuntu/hf_env/lib/python3.8/site-packages/torch/utils/checkpoint.py:31: UserWarning: None of the inputs have requires_grad=True. Gradients will be None
+  warnings.warn("None of the inputs have requires_grad=True. Gradients will be None")
+
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 83%|████████▎ | 5000/6000 [18:07:06<2:19:04,  8.34s/it][INFO|trainer.py:2955] 2022-12-15 12:04:43,656 >> ***** Running Evaluation *****
+[INFO|trainer.py:2959] 2022-12-15 12:04:43,656 >>   Num examples: Unknown
+[INFO|trainer.py:2960] 2022-12-15 12:04:43,656 >>   Batch size = 32
+{'loss': 0.0735, 'learning_rate': 1.8952727272727272e-06, 'epoch': 10.0}
+{'loss': 0.0715, 'learning_rate': 1.8589090909090909e-06, 'epoch': 10.01}
+{'loss': 0.0705, 'learning_rate': 1.8225454545454543e-06, 'epoch': 10.01}
+{'loss': 0.0586, 'learning_rate': 1.786181818181818e-06, 'epoch': 10.01}
+{'loss': 0.0556, 'learning_rate': 1.7498181818181817e-06, 'epoch': 10.02}
+{'loss': 0.0543, 'learning_rate': 1.7134545454545456e-06, 'epoch': 10.02}
+{'loss': 0.053, 'learning_rate': 1.677090909090909e-06, 'epoch': 10.03}
+{'loss': 0.0578, 'learning_rate': 1.6407272727272727e-06, 'epoch': 10.03}
+{'loss': 0.0944, 'learning_rate': 1.6043636363636364e-06, 'epoch': 10.04}
+{'loss': 0.0829, 'learning_rate': 1.568e-06, 'epoch': 10.04}
+{'loss': 0.0856, 'learning_rate': 1.5316363636363635e-06, 'epoch': 10.04}
+{'loss': 0.0906, 'learning_rate': 1.4952727272727272e-06, 'epoch': 10.05}
+{'loss': 0.096, 'learning_rate': 1.4589090909090909e-06, 'epoch': 10.05}
+
+
+
+[INFO|trainer_utils.py:689] 2022-12-15 12:04:49,266 >> 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.
+
                                                        
 83%|████████▎ | 5000/6000 [19:30:49<2:19:04,  8.34s/it][INFO|trainer.py:2700] 2022-12-15 13:28:25,917 >> Saving model checkpoint to ./checkpoint-5000
+[INFO|configuration_utils.py:447] 2022-12-15 13:28:25,918 >> Configuration saved in ./checkpoint-5000/config.json
+[INFO|modeling_utils.py:1680] 2022-12-15 13:28:26,805 >> Model weights saved in ./checkpoint-5000/pytorch_model.bin
+[INFO|feature_extraction_utils.py:368] 2022-12-15 13:28:26,820 >> Feature extractor saved in ./checkpoint-5000/preprocessor_config.json
+[INFO|feature_extraction_utils.py:368] 2022-12-15 13:28:30,634 >> Feature extractor saved in ./preprocessor_config.json

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