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openai/whisper-small

This model is a fine-tuned version of openai/whisper-small on the pphuc25/VietMed-split-8-2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9411
  • Wer: 24.8801
  • Cer: 21.1598

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
0.5524 1.0 569 0.5578 28.6033 24.0945
0.3686 2.0 1138 0.5504 30.1336 26.4337
0.2033 3.0 1707 0.6189 28.4239 24.3193
0.0994 4.0 2276 0.7076 26.9339 22.6996
0.0404 5.0 2845 0.7609 26.8827 22.0729
0.0317 6.0 3414 0.7954 27.0108 23.2898
0.0254 7.0 3983 0.8337 26.8534 22.7960
0.0118 8.0 4552 0.8676 28.1091 23.5103
0.016 9.0 5121 0.8757 25.6928 21.6242
0.0072 10.0 5690 0.8893 25.2169 21.3377
0.0032 11.0 6259 0.9026 24.7593 20.8569
0.0047 12.0 6828 0.9188 26.1798 22.3055
0.002 13.0 7397 0.9011 25.7844 22.0373
0.0005 14.0 7966 0.9134 25.6745 21.8073
0.0004 15.0 8535 0.9110 25.4000 21.5877
0.0001 16.0 9104 0.9231 24.6971 20.8421
0.0001 17.0 9673 0.9301 25.1766 21.4002
0.0001 18.0 10242 0.9363 24.8984 21.1641
0.0001 19.0 10811 0.9399 24.8398 21.1155
0.0 20.0 11380 0.9411 24.8801 21.1598

Framework versions

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