whisper-synthesized-turkish-4-hour-hlr
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: 0.4388
- Wer: 15.4240
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: 0.0001
- 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 |
|---|---|---|---|---|
| 0.7343 | 1.04 | 100 | 0.2580 | 16.7757 |
| 0.1568 | 2.08 | 200 | 0.2714 | 15.3129 |
| 0.091 | 3.12 | 300 | 0.3099 | 16.2573 |
| 0.0861 | 4.17 | 400 | 0.3946 | 22.9910 |
| 0.0967 | 5.21 | 500 | 0.4884 | 23.2132 |
| 0.0775 | 6.25 | 600 | 0.4263 | 19.9852 |
| 0.0692 | 7.29 | 700 | 0.4428 | 20.0099 |
| 0.052 | 8.33 | 800 | 0.4407 | 23.6761 |
| 0.0458 | 9.38 | 900 | 0.4760 | 19.7445 |
| 0.0326 | 10.42 | 1000 | 0.4847 | 18.6520 |
| 0.0281 | 11.46 | 1100 | 0.4936 | 20.2074 |
| 0.0221 | 12.5 | 1200 | 0.4655 | 19.3495 |
| 0.0123 | 13.54 | 1300 | 0.4657 | 17.5781 |
| 0.0105 | 14.58 | 1400 | 0.4493 | 16.2264 |
| 0.0042 | 15.62 | 1500 | 0.4396 | 15.5660 |
| 0.0029 | 16.67 | 1600 | 0.4412 | 15.7882 |
| 0.0011 | 17.71 | 1700 | 0.4400 | 15.8190 |
| 0.0005 | 18.75 | 1800 | 0.4400 | 15.4672 |
| 0.0003 | 19.79 | 1900 | 0.4389 | 15.4117 |
| 0.0002 | 20.83 | 2000 | 0.4388 | 15.4240 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3