Whisper Tiny En - speechocean762
This model is a fine-tuned version of openai/whisper-tiny.en on the speechocean762 dataset. It achieves the following results on the evaluation set (Best results):
- Loss: 0.6837
- Wer: 28.3422
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: 128
- 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: 250
- training_steps: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.0683 | 0.2778 | 10 | 4.0618 | 38.3139 |
| 3.9216 | 0.5556 | 20 | 3.8951 | 37.4961 |
| 3.7275 | 0.8333 | 30 | 3.6337 | 45.8635 |
| 3.3621 | 1.1111 | 40 | 3.2960 | 36.4580 |
| 2.9818 | 1.3889 | 50 | 2.8749 | 40.7046 |
| 2.5404 | 1.6667 | 60 | 2.3590 | 44.1648 |
| 1.9537 | 1.9444 | 70 | 1.7972 | 49.4495 |
| 1.4184 | 2.2222 | 80 | 1.3603 | 66.3731 |
| 1.1875 | 2.5 | 90 | 1.1660 | 55.5206 |
| 1.1203 | 2.7778 | 100 | 1.0743 | 44.8569 |
| 1.024 | 3.0556 | 110 | 1.0085 | 44.2277 |
| 0.905 | 3.3333 | 120 | 0.9581 | 42.4347 |
| 0.8787 | 3.6111 | 130 | 0.9169 | 40.9877 |
| 0.8677 | 3.8889 | 140 | 0.8844 | 37.2130 |
| 0.7563 | 4.1667 | 150 | 0.8573 | 36.4895 |
| 0.7497 | 4.4444 | 160 | 0.8324 | 35.9862 |
| 0.7283 | 4.7222 | 170 | 0.8097 | 35.2941 |
| 0.7055 | 5.0 | 180 | 0.7907 | 30.6071 |
| 0.6259 | 5.2778 | 190 | 0.7770 | 30.9531 |
| 0.6115 | 5.5556 | 200 | 0.7601 | 30.3555 |
| 0.5998 | 5.8333 | 210 | 0.7457 | 29.8207 |
| 0.5752 | 6.1111 | 220 | 0.7368 | 29.9465 |
| 0.5031 | 6.3889 | 230 | 0.7284 | 29.7892 |
| 0.5079 | 6.6667 | 240 | 0.7140 | 29.0028 |
| 0.4969 | 6.9444 | 250 | 0.7006 | 29.3174 |
| 0.4285 | 7.2222 | 260 | 0.6951 | 32.5889 |
| 0.466 | 7.5 | 270 | 0.6886 | 31.6766 |
| 0.4101 | 7.7778 | 280 | 0.6837 | 28.3422 |
| 0.4021 | 8.0556 | 290 | 0.6755 | 31.4250 |
| 0.359 | 8.3333 | 300 | 0.6763 | 32.5260 |
| 0.3281 | 8.6111 | 310 | 0.6727 | 32.2114 |
| 0.3604 | 8.8889 | 320 | 0.6695 | 36.1120 |
| 0.3085 | 9.1667 | 330 | 0.6698 | 32.1799 |
| 0.3007 | 9.4444 | 340 | 0.6698 | 32.3372 |
| 0.3313 | 9.7222 | 350 | 0.6659 | 35.7974 |
| 0.2862 | 10.0 | 360 | 0.6638 | 32.0226 |
| 0.278 | 10.2778 | 370 | 0.6639 | 31.9912 |
| 0.2645 | 10.5556 | 380 | 0.6639 | 32.0856 |
| 0.2708 | 10.8333 | 390 | 0.6649 | 32.0541 |
| 0.257 | 11.1111 | 400 | 0.6620 | 32.1799 |
| 0.2455 | 11.3889 | 410 | 0.6621 | 31.8025 |
| 0.2506 | 11.6667 | 420 | 0.6636 | 38.9745 |
| 0.2545 | 11.9444 | 430 | 0.6635 | 38.9116 |
| 0.2266 | 12.2222 | 440 | 0.6644 | 31.8339 |
| 0.2072 | 12.5 | 450 | 0.6652 | 32.1799 |
| 0.2382 | 12.7778 | 460 | 0.6661 | 31.9597 |
| 0.219 | 13.0556 | 470 | 0.6653 | 38.7858 |
| 0.2256 | 13.3333 | 480 | 0.6649 | 38.9431 |
| 0.2178 | 13.6111 | 490 | 0.6652 | 38.9431 |
| 0.2229 | 13.8889 | 500 | 0.6654 | 38.8487 |
Framework versions
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.2.dev0
- Tokenizers 0.19.1