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whisper_final_nosp

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: 0.0732
  • Train Accuracy: 0.0234
  • Validation Loss: 0.8512
  • Validation Accuracy: 0.0203
  • 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
7.5559 0.0010 6.3853 0.0013 0
6.3227 0.0021 5.7023 0.0038 1
4.9825 0.0063 3.6302 0.0109 2
2.9413 0.0126 2.1959 0.0154 3
1.9349 0.0157 1.6630 0.0172 4
1.4741 0.0171 1.3813 0.0181 5
1.1975 0.0181 1.2161 0.0186 6
1.0048 0.0188 1.0990 0.0191 7
0.8598 0.0194 1.0165 0.0194 8
0.7431 0.0199 0.9603 0.0196 9
0.6489 0.0203 0.9106 0.0198 10
0.5682 0.0207 0.8787 0.0199 11
0.4985 0.0210 0.8548 0.0200 12
0.4372 0.0213 0.8352 0.0201 13
0.3829 0.0216 0.8190 0.0202 14
0.3327 0.0219 0.8148 0.0202 15
0.2904 0.0221 0.8139 0.0202 16
0.2492 0.0224 0.8188 0.0202 17
0.2140 0.0226 0.8146 0.0203 18
0.1825 0.0228 0.8115 0.0203 19
0.1538 0.0229 0.8228 0.0203 20
0.1293 0.0231 0.8341 0.0202 21
0.1070 0.0232 0.8404 0.0202 22
0.0889 0.0233 0.8569 0.0202 23
0.0732 0.0234 0.8512 0.0203 24

Framework versions

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