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openai/whisper-tiny

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

  • Loss: 1.4458
  • Wer: 91.7485

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
0.9094 1.0 161 1.0980 107.4656
0.5868 2.0 322 1.1400 169.7446
0.3831 3.0 483 1.1572 103.7328
0.1839 4.0 644 1.2091 99.2141
0.1032 5.0 805 1.2858 99.6071
0.0669 6.0 966 1.3358 94.3026
0.0445 7.0 1127 1.3355 95.6778
0.0279 8.0 1288 1.3960 93.1238
0.0218 9.0 1449 1.3946 95.4813
0.0163 10.0 1610 1.4312 91.7485
0.007 11.0 1771 1.4203 94.6955
0.0049 12.0 1932 1.4495 92.1415
0.0045 13.0 2093 1.4258 92.7308
0.0029 14.0 2254 1.4203 92.7308
0.0036 15.0 2415 1.4382 91.5521
0.0023 16.0 2576 1.4340 91.3556
0.0009 17.0 2737 1.4496 91.3556
0.0009 18.0 2898 1.4467 92.7308
0.0007 19.0 3059 1.4446 91.9450
0.0006 20.0 3220 1.4458 91.7485

Framework versions

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