Whisper-medium-BTC
This model is a fine-tuned version of openai/whisper-medium.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3875
- Wer: 6.5315
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: 3e-06
- train_batch_size: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- training_steps: 800
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7348 | 2.01 | 50 | 0.7378 | 9.3091 |
| 0.5276 | 4.02 | 100 | 0.5290 | 8.6125 |
| 0.3585 | 7.0 | 150 | 0.3875 | 6.5315 |
| 0.2924 | 9.01 | 200 | 0.3548 | 6.6779 |
| 0.2506 | 11.02 | 250 | 0.3364 | 6.7888 |
| 0.1946 | 14.01 | 300 | 0.3262 | 7.1482 |
| 0.1411 | 16.02 | 350 | 0.3329 | 7.2104 |
| 0.1005 | 19.0 | 400 | 0.3422 | 7.5565 |
| 0.0535 | 21.01 | 450 | 0.3532 | 7.1793 |
| 0.0259 | 23.02 | 500 | 0.3456 | 7.5121 |
| 0.0137 | 26.0 | 550 | 0.3587 | 7.6541 |
| 0.0078 | 28.02 | 600 | 0.3591 | 7.3524 |
| 0.0041 | 30.02 | 650 | 0.3672 | 7.3035 |
| 0.0026 | 33.01 | 700 | 0.3962 | 7.3213 |
| 0.0022 | 35.02 | 750 | 0.3997 | 7.3524 |
| 0.0022 | 38.0 | 800 | 0.4025 | 7.3302 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
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