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Upload TFWhisperForConditionalGeneration
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metadata
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_keras_callback
model-index:
  - name: train_from_raw_cv12_true__0015
    results: []

train_from_raw_cv12_true__0015

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: 0.2922
  • Train Accuracy: 0.1013
  • Train Wermet: 3.5614
  • Validation Loss: 0.3391
  • Validation Accuracy: 0.0623
  • Validation Wermet: 9.6152
  • Epoch: 14

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

Framework versions

  • Transformers 4.33.0.dev0
  • TensorFlow 2.13.0
  • Tokenizers 0.13.3