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metadata
language:
  - zh
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: openai/whisper-small
    results: []

openai/whisper-small

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

  • Loss: 1.1189
  • Wer: 80.7466
  • Cer: 23.1952

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 Cer
0.6947 1.0 161 0.8771 224.7544 75.6462
0.3688 2.0 322 0.8461 107.2692 32.0187
0.2168 3.0 483 0.9040 84.8723 26.0472
0.1117 4.0 644 0.9532 90.5697 28.1640
0.0928 5.0 805 0.9663 89.7839 28.2977
0.0672 6.0 966 1.0584 87.2299 31.1275
0.0534 7.0 1127 1.0810 86.4440 28.5651
0.0443 8.0 1288 1.0709 83.8900 29.1889
0.0415 9.0 1449 1.0984 85.0688 26.4929
0.0198 10.0 1610 1.1180 89.9804 27.3841
0.0182 11.0 1771 1.0824 86.4440 27.1613
0.0116 12.0 1932 1.1320 85.6582 26.1809
0.0107 13.0 2093 1.1042 82.5147 24.6658
0.0075 14.0 2254 1.1034 80.9430 24.5989
0.0021 15.0 2415 1.0967 78.9784 23.3734
0.0003 16.0 2576 1.1061 81.1395 23.4848
0.0002 17.0 2737 1.1144 81.1395 23.5294
0.0002 18.0 2898 1.1173 81.1395 23.3957
0.0004 19.0 3059 1.1184 80.7466 23.1506
0.0003 20.0 3220 1.1189 80.7466 23.1952

Framework versions

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