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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: 0.9256
  • Wer: 24.4737
  • Cer: 20.2163

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
0.5664 1.0 569 0.5651 25.4000 20.5826
0.3901 2.0 1138 0.5406 24.0271 19.6035
0.2343 3.0 1707 0.5885 23.4413 19.3336
0.145 4.0 2276 0.6539 23.9026 20.0783
0.0675 5.0 2845 0.7298 26.7875 22.1606
0.0549 6.0 3414 0.7806 27.5892 22.7204
0.0339 7.0 3983 0.7988 32.2350 31.3005
0.0249 8.0 4552 0.8216 32.5133 28.8528
0.016 9.0 5121 0.8464 27.9590 23.8089
0.0107 10.0 5690 0.8647 27.1060 21.7405
0.0112 11.0 6259 0.8650 28.1896 23.1761
0.0102 12.0 6828 0.8800 27.4831 23.1258
0.0025 13.0 7397 0.8910 25.2828 21.4575
0.0021 14.0 7966 0.8998 26.4397 21.8012
0.0049 15.0 8535 0.8959 26.6081 23.5693
0.0001 16.0 9104 0.9047 24.2907 19.6070
0.0001 17.0 9673 0.9104 25.1400 20.7102
0.0004 18.0 10242 0.9198 24.9350 20.5557
0.0 19.0 10811 0.9243 24.0893 19.7025
0.0 20.0 11380 0.9256 24.4737 20.2163

Framework versions

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