whisper_charsplit_new_0032

This model is a fine-tuned version of openai/whisper-tiny on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.0043
  • Train Accuracy: 0.0795
  • Train Wermet: 10.9497
  • Validation Loss: 0.4525
  • Validation Accuracy: 0.0761
  • Validation Wermet: 9.3202
  • Epoch: 31

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 1e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Train Accuracy Train Wermet Validation Loss Validation Accuracy Validation Wermet Epoch
0.8733 0.0602 13.0686 0.6470 0.0676 11.4066 0
0.5740 0.0666 12.7778 0.5113 0.0706 11.1022 1
0.4553 0.0692 12.2404 0.4371 0.0723 10.9105 2
0.3813 0.0708 11.9157 0.3935 0.0733 9.4615 3
0.3292 0.0720 11.5732 0.3630 0.0740 9.9885 4
0.2886 0.0729 11.5171 0.3403 0.0745 9.8042 5
0.2561 0.0736 11.3173 0.3256 0.0749 9.9431 6
0.2282 0.0743 11.7308 0.3159 0.0752 9.2086 7
0.2036 0.0748 11.4503 0.3071 0.0754 9.5236 8
0.1820 0.0754 11.7175 0.3005 0.0756 10.0755 9
0.1628 0.0758 11.7056 0.2993 0.0757 9.9497 10
0.1450 0.0762 11.7637 0.2971 0.0758 10.1481 11
0.1287 0.0766 11.8509 0.3029 0.0759 10.2042 12
0.1140 0.0770 12.1100 0.3004 0.0760 10.3873 13
0.0998 0.0773 11.9502 0.3025 0.0761 10.7066 14
0.0872 0.0777 12.3196 0.3129 0.0759 10.7707 15
0.0760 0.0779 12.2637 0.3142 0.0761 10.2638 16
0.0651 0.0782 12.1215 0.3192 0.0761 10.0750 17
0.0547 0.0785 12.0551 0.3294 0.0761 10.4732 18
0.0463 0.0787 11.9677 0.3402 0.0760 10.2814 19
0.0386 0.0789 11.6855 0.3517 0.0760 10.0599 20
0.0318 0.0790 11.6314 0.3628 0.0760 9.6652 21
0.0262 0.0792 11.4603 0.3728 0.0760 10.0035 22
0.0224 0.0792 11.4330 0.3824 0.0760 9.1995 23
0.0181 0.0793 11.3124 0.3982 0.0759 9.8710 24
0.0142 0.0794 11.3562 0.4057 0.0760 9.6831 25
0.0118 0.0794 11.0532 0.4207 0.0759 9.7227 26
0.0101 0.0794 11.2963 0.4282 0.0760 9.5792 27
0.0114 0.0794 11.3093 0.4431 0.0758 9.5545 28
0.0109 0.0794 11.4214 0.4419 0.0760 9.4377 29
0.0084 0.0794 10.9143 0.4474 0.0760 9.3668 30
0.0043 0.0795 10.9497 0.4525 0.0761 9.3202 31

Framework versions

  • Transformers 4.32.0.dev0
  • TensorFlow 2.12.0
  • Tokenizers 0.13.3
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