whisper-synthesized-turkish-2-hour
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: 0.3457
- Wer: 20.3461
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.3076 | 2.08 | 100 | 0.6286 | 96.2530 |
| 0.421 | 4.17 | 200 | 0.4269 | 22.7088 |
| 0.1585 | 6.25 | 300 | 0.2911 | 22.3150 |
| 0.0482 | 8.33 | 400 | 0.3047 | 16.6706 |
| 0.022 | 10.42 | 500 | 0.3086 | 16.5752 |
| 0.013 | 12.5 | 600 | 0.3209 | 19.7613 |
| 0.0049 | 14.58 | 700 | 0.3185 | 16.1575 |
| 0.0025 | 16.67 | 800 | 0.3278 | 16.7303 |
| 0.0019 | 18.75 | 900 | 0.3239 | 20.5012 |
| 0.0019 | 20.83 | 1000 | 0.3307 | 19.7613 |
| 0.0011 | 22.92 | 1100 | 0.3329 | 20.5728 |
| 0.0008 | 25.0 | 1200 | 0.3361 | 20.5609 |
| 0.0007 | 27.08 | 1300 | 0.3383 | 20.3341 |
| 0.0006 | 29.17 | 1400 | 0.3403 | 20.2029 |
| 0.0006 | 31.25 | 1500 | 0.3418 | 20.3699 |
| 0.0006 | 33.33 | 1600 | 0.3432 | 20.0477 |
| 0.0005 | 35.42 | 1700 | 0.3442 | 20.0835 |
| 0.0005 | 37.5 | 1800 | 0.3450 | 20.1313 |
| 0.0005 | 39.58 | 1900 | 0.3454 | 20.3699 |
| 0.0005 | 41.67 | 2000 | 0.3457 | 20.3461 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3