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whisper_final_09

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: 0.0816
  • Train Accuracy: 0.0343
  • Validation Loss: 0.5877
  • Validation Accuracy: 0.0313
  • Epoch: 24

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 Validation Loss Validation Accuracy Epoch
5.0832 0.0116 4.4298 0.0124 0
4.3130 0.0131 4.0733 0.0141 1
3.9211 0.0146 3.6762 0.0157 2
3.5505 0.0159 3.3453 0.0171 3
3.1592 0.0175 2.8062 0.0199 4
2.2581 0.0220 1.7622 0.0252 5
1.4671 0.0259 1.2711 0.0276 6
1.0779 0.0278 1.0220 0.0288 7
0.8591 0.0290 0.8836 0.0295 8
0.7159 0.0297 0.7918 0.0300 9
0.6105 0.0304 0.7276 0.0303 10
0.5287 0.0309 0.6850 0.0306 11
0.4614 0.0313 0.6472 0.0308 12
0.4049 0.0317 0.6199 0.0310 13
0.3562 0.0320 0.6019 0.0311 14
0.3139 0.0324 0.5868 0.0311 15
0.2766 0.0326 0.5751 0.0312 16
0.2438 0.0329 0.5701 0.0312 17
0.2116 0.0332 0.5686 0.0313 18
0.1844 0.0334 0.5619 0.0313 19
0.1593 0.0336 0.5710 0.0313 20
0.1363 0.0338 0.5656 0.0314 21
0.1160 0.0340 0.5763 0.0313 22
0.0981 0.0341 0.5806 0.0313 23
0.0816 0.0343 0.5877 0.0313 24

Framework versions

  • Transformers 4.25.0.dev0
  • TensorFlow 2.9.2
  • Datasets 2.6.1
  • Tokenizers 0.13.2
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