whisper-synthesized-turkish-4-hour-llr
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: 0.2356
- Wer: 14.9179
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-06
- 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 |
|---|---|---|---|---|
| 1.8278 | 1.04 | 100 | 1.5357 | 41.2110 |
| 1.2048 | 2.08 | 200 | 0.8059 | 86.3165 |
| 0.6206 | 3.12 | 300 | 0.5751 | 94.1612 |
| 0.4927 | 4.17 | 400 | 0.5024 | 80.1568 |
| 0.4277 | 5.21 | 500 | 0.4451 | 48.6607 |
| 0.3502 | 6.25 | 600 | 0.3999 | 32.7490 |
| 0.2948 | 7.29 | 700 | 0.3650 | 21.5961 |
| 0.24 | 8.33 | 800 | 0.3344 | 17.7756 |
| 0.2079 | 9.38 | 900 | 0.3010 | 15.2512 |
| 0.1416 | 10.42 | 1000 | 0.2402 | 13.8687 |
| 0.1076 | 11.46 | 1100 | 0.2357 | 14.4427 |
| 0.0905 | 12.5 | 1200 | 0.2350 | 14.0415 |
| 0.0759 | 13.54 | 1300 | 0.2348 | 14.0230 |
| 0.0819 | 14.58 | 1400 | 0.2345 | 14.0600 |
| 0.0608 | 15.62 | 1500 | 0.2346 | 14.3563 |
| 0.0712 | 16.67 | 1600 | 0.2350 | 14.2575 |
| 0.0608 | 17.71 | 1700 | 0.2355 | 14.8562 |
| 0.0632 | 18.75 | 1800 | 0.2354 | 14.9241 |
| 0.0544 | 19.79 | 1900 | 0.2356 | 14.9303 |
| 0.0529 | 20.83 | 2000 | 0.2356 | 14.9179 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3