whisper-small-af-ZA
This model is a fine-tuned version of openai/whisper-small on the google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 0.5728
- Wer: 0.3664
- Wer Ortho: 0.3943
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: constant_with_warmup
- lr_scheduler_warmup_steps: 5
- training_steps: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Wer Ortho |
|---|---|---|---|---|---|
| 0.7731 | 1.45 | 100 | 0.7280 | 0.3740 | 0.3863 |
| 0.2103 | 2.9 | 200 | 0.5116 | 0.3661 | 0.3859 |
| 0.0633 | 4.35 | 300 | 0.4967 | 0.2810 | 0.3008 |
| 0.0249 | 5.8 | 400 | 0.5003 | 0.3299 | 0.3477 |
| 0.0143 | 7.25 | 500 | 0.5191 | 0.3510 | 0.3660 |
| 0.0053 | 8.7 | 600 | 0.5149 | 0.3070 | 0.3221 |
| 0.0035 | 10.14 | 700 | 0.5345 | 0.3266 | 0.3443 |
| 0.0027 | 11.59 | 800 | 0.5339 | 0.3175 | 0.3344 |
| 0.0026 | 13.04 | 900 | 0.5435 | 0.3134 | 0.3328 |
| 0.0037 | 14.49 | 1000 | 0.5346 | 0.2506 | 0.2714 |
| 0.0045 | 15.94 | 1100 | 0.5438 | 0.3220 | 0.3389 |
| 0.0028 | 17.39 | 1200 | 0.5588 | 0.2551 | 0.2740 |
| 0.0036 | 18.84 | 1300 | 0.5466 | 0.2728 | 0.2702 |
| 0.0035 | 20.29 | 1400 | 0.5364 | 0.3119 | 0.3332 |
| 0.0056 | 21.74 | 1500 | 0.5608 | 0.2506 | 0.2721 |
| 0.0037 | 23.19 | 1600 | 0.5443 | 0.2833 | 0.3027 |
| 0.0035 | 24.64 | 1700 | 0.5466 | 0.3631 | 0.3866 |
| 0.0024 | 26.09 | 1800 | 0.5628 | 0.3198 | 0.3416 |
| 0.0036 | 27.54 | 1900 | 0.5495 | 0.2946 | 0.3122 |
| 0.0016 | 28.99 | 2000 | 0.5728 | 0.3664 | 0.3943 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 1.12.1+cu116
- Datasets 2.4.0
- Tokenizers 0.12.1