Whisper Medium Dv - Leon Lee
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 13 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2803
- Wer Ortho: 48.8335
- Wer: 8.4327
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 8000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.1344 | 0.8157 | 500 | 0.1613 | 59.9206 | 12.1049 |
0.0732 | 1.6313 | 1000 | 0.1382 | 52.9285 | 10.2271 |
0.0411 | 2.4470 | 1500 | 0.1447 | 52.3087 | 9.7628 |
0.0244 | 3.2626 | 2000 | 0.1538 | 51.6749 | 9.4534 |
0.0164 | 4.0783 | 2500 | 0.1839 | 53.8617 | 9.4290 |
0.0162 | 4.8940 | 3000 | 0.1734 | 51.7863 | 9.0604 |
0.0086 | 5.7096 | 3500 | 0.1962 | 50.8949 | 9.0222 |
0.0048 | 6.5253 | 4000 | 0.2299 | 50.7904 | 8.8205 |
0.003 | 7.3409 | 4500 | 0.2336 | 50.7487 | 8.8344 |
0.0017 | 8.1566 | 5000 | 0.2303 | 50.2472 | 8.6275 |
0.0017 | 8.9723 | 5500 | 0.2455 | 49.9896 | 8.6327 |
0.0005 | 9.7879 | 6000 | 0.2551 | 49.8015 | 8.5371 |
0.0001 | 10.6036 | 6500 | 0.2682 | 48.8962 | 8.4414 |
0.0 | 11.4192 | 7000 | 0.2732 | 48.6663 | 8.4206 |
0.0 | 12.2349 | 7500 | 0.2800 | 48.8892 | 8.4605 |
0.0 | 13.0506 | 8000 | 0.2803 | 48.8335 | 8.4327 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
openai/whisper-medium