whisper-small-yoruba-07-17
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3346
- Wer Ortho: 34.5068
- Wer: 25.6765
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: 16
- 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: 50
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.7951 | 0.0745 | 250 | 0.8000 | 60.4651 | 45.9597 |
| 0.605 | 0.1490 | 500 | 0.6408 | 50.3176 | 39.3120 |
| 0.5273 | 0.2235 | 750 | 0.5621 | 45.8657 | 35.7526 |
| 0.4483 | 0.2980 | 1000 | 0.5138 | 43.4349 | 33.8902 |
| 0.4158 | 0.3725 | 1250 | 0.4752 | 41.9130 | 32.5295 |
| 0.4032 | 0.4470 | 1500 | 0.4434 | 41.1866 | 31.6249 |
| 0.3261 | 0.5215 | 1750 | 0.4153 | 40.2187 | 30.3193 |
| 0.3606 | 0.5959 | 2000 | 0.3910 | 38.0659 | 29.1049 |
| 0.3008 | 0.6704 | 2250 | 0.3769 | 36.7084 | 27.5409 |
| 0.2938 | 0.7449 | 2500 | 0.3608 | 36.2985 | 27.0924 |
| 0.2933 | 0.8194 | 2750 | 0.3494 | 35.6086 | 27.0448 |
| 0.277 | 0.8939 | 3000 | 0.3404 | 34.5474 | 25.5682 |
| 0.2849 | 0.9684 | 3250 | 0.3346 | 34.5068 | 25.6765 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1