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openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the Hanhpt23/GermanMed dataset. It achieves the following results on the evaluation set:

  • Loss: 5.4320
  • Wer: 104.7646

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:

  • learning_rate: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 100
  • num_epochs: 20

Training results

Training Loss Epoch Step Validation Loss Wer
3.0357 1.0 765 3.6479 111.4811
2.0376 2.0 1530 3.7281 105.4535
1.1924 3.0 2295 4.1208 101.4351
0.5922 4.0 3060 4.3857 100.8611
0.3146 5.0 3825 4.6652 101.6648
0.252 6.0 4590 4.7717 102.4684
0.1758 7.0 5355 4.9846 114.6383
0.1637 8.0 6120 5.0070 103.1573
0.1727 9.0 6885 5.0401 118.6567
0.1175 10.0 7650 5.1600 101.5499
0.1276 11.0 8415 5.1986 105.2239
0.1214 12.0 9180 5.2462 101.0907
0.1314 13.0 9945 5.2108 123.8232
0.0995 14.0 10710 5.3113 103.6165
0.1142 15.0 11475 5.3306 108.7256
0.1005 16.0 12240 5.3449 102.9277
0.0911 17.0 13005 5.4078 101.9518
0.0826 18.0 13770 5.3547 104.1332
0.0976 19.0 14535 5.3862 106.6590
0.0996 20.0 15300 5.4320 104.7646

Framework versions

  • Transformers 4.41.1
  • Pytorch 2.3.0
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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