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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: 1.5036
  • Cer: 34.0018

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 Cer
0.9949 1.0 161 1.1720 86.6756
0.6345 2.0 322 1.2101 74.7772
0.4273 3.0 483 1.2770 42.6025
0.2435 4.0 644 1.3652 44.5856
0.1437 5.0 805 1.4654 50.7353
0.097 6.0 966 1.4137 53.5873
0.0808 7.0 1127 1.4085 42.1569
0.049 8.0 1288 1.4790 38.6586
0.0392 9.0 1449 1.5276 40.6640
0.0283 10.0 1610 1.4854 42.5802
0.0164 11.0 1771 1.5004 39.7727
0.0126 12.0 1932 1.5267 41.9118
0.0124 13.0 2093 1.5349 36.7870
0.0061 14.0 2254 1.5172 35.6061
0.0018 15.0 2415 1.5075 34.0909
0.0032 16.0 2576 1.5066 34.5365
0.001 17.0 2737 1.4948 33.6453
0.0007 18.0 2898 1.5060 34.3137
0.0005 19.0 3059 1.5030 34.2246
0.0005 20.0 3220 1.5036 34.0018

Framework versions

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