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train_from_raw_cv12_true__0030

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: 0.0227
  • Train Accuracy: 0.1110
  • Train Wermet: 3.7827
  • Validation Loss: 0.3579
  • Validation Accuracy: 0.0641
  • Validation Wermet: 10.2859
  • Epoch: 29

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': 2e-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
2.3396 0.0444 2.7124 1.8124 0.0331 9.4418 0
1.7496 0.0562 3.2708 1.6529 0.0359 9.7805 1
1.6254 0.0594 3.1714 1.5874 0.0371 10.4139 2
1.5490 0.0615 3.0208 1.5102 0.0382 8.2054 3
1.4910 0.0631 2.8298 1.4213 0.0402 8.9930 4
1.4233 0.0650 2.7100 1.3319 0.0421 8.8483 5
1.3203 0.0679 2.5125 1.1806 0.0450 7.0373 6
1.1453 0.0730 2.5001 1.0029 0.0484 5.7328 7
0.9537 0.0789 2.6295 0.7799 0.0529 6.7373 8
0.7822 0.0844 2.7501 0.6499 0.0556 8.5538 9
0.6317 0.0895 2.9507 0.5467 0.0578 8.4990 10
0.5010 0.0940 3.1604 0.4597 0.0597 9.4002 11
0.4026 0.0975 3.2910 0.3984 0.0610 9.8173 12
0.3372 0.0998 3.5302 0.3571 0.0619 9.6433 13
0.2922 0.1013 3.5614 0.3391 0.0623 9.6152 14
0.2572 0.1025 3.5685 0.3157 0.0628 9.4497 15
0.2258 0.1036 3.5179 0.3104 0.0630 9.7735 16
0.1995 0.1045 3.5362 0.2944 0.0634 9.8154 17
0.1762 0.1054 3.5227 0.2820 0.0637 9.8672 18
0.1551 0.1061 3.5489 0.2849 0.0638 9.6569 19
0.1356 0.1068 3.4990 0.2821 0.0639 9.9735 20
0.1174 0.1074 3.5119 0.2841 0.0640 9.8770 21
0.1016 0.1080 3.5233 0.2903 0.0640 10.0309 22
0.0847 0.1087 3.5368 0.3013 0.0640 9.8095 23
0.0713 0.1092 3.5250 0.3040 0.0640 9.7686 24
0.0596 0.1096 3.5310 0.3137 0.0640 9.9239 25
0.0478 0.1101 3.5776 0.3228 0.0641 10.2774 26
0.0400 0.1104 3.6155 0.3316 0.0641 9.9082 27
0.0301 0.1107 3.6545 0.3446 0.0641 9.9672 28
0.0227 0.1110 3.7827 0.3579 0.0641 10.2859 29

Framework versions

  • Transformers 4.33.0.dev0
  • TensorFlow 2.13.0
  • Tokenizers 0.13.3
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