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openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the pphuc25/EngMed dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1935
  • Wer: 27.2679

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
0.5346 1.0 323 0.6308 30.4852
0.2978 2.0 646 0.7524 25.0527
0.1478 3.0 969 0.7934 29.2194
0.1208 4.0 1292 0.8305 34.0190
0.0667 5.0 1615 0.8781 22.2046
0.0562 6.0 1938 1.0234 27.0042
0.0519 7.0 2261 0.9954 17.1941
0.0311 8.0 2584 1.0153 35.2321
0.0183 9.0 2907 1.1135 48.5759
0.015 10.0 3230 1.1428 35.6540
0.0099 11.0 3553 1.1355 39.3987
0.0054 12.0 3876 1.1408 27.3207
0.0037 13.0 4199 1.1651 28.6920
0.0024 14.0 4522 1.1648 40.2954
0.0004 15.0 4845 1.1480 44.0401
0.0004 16.0 5168 1.1564 23.1540
0.0003 17.0 5491 1.1754 28.2173
0.0007 18.0 5814 1.1884 26.0021
0.0001 19.0 6137 1.1925 27.9536
0.0001 20.0 6460 1.1935 27.2679

Framework versions

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