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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Base model
openai/whisper-small