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metadata
language:
  - vi
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/VietMed-split-8-2 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9118
  • Wer: 21.7024

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
0.6339 1.0 569 0.6214 27.8675
0.4322 2.0 1138 0.5860 25.1949
0.2846 3.0 1707 0.6092 24.0564
0.1624 4.0 2276 0.6697 24.2614
0.0915 5.0 2845 0.7291 25.9162
0.0642 6.0 3414 0.7756 24.7739
0.0382 7.0 3983 0.8095 24.1955
0.0355 8.0 4552 0.8362 24.2541
0.0314 9.0 5121 0.8388 23.9063
0.0174 10.0 5690 0.8719 22.9251
0.0107 11.0 6259 0.8740 23.0899
0.0109 12.0 6828 0.8811 22.8226
0.0036 13.0 7397 0.8770 22.5700
0.0037 14.0 7966 0.8888 22.4382
0.002 15.0 8535 0.8917 22.3467
0.0001 16.0 9104 0.9047 22.0099
0.0004 17.0 9673 0.8960 21.9660
0.0009 18.0 10242 0.9079 21.6914
0.0001 19.0 10811 0.9108 21.6658
0.0 20.0 11380 0.9118 21.7024

Framework versions

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