whisper-small-mn-8
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: 0.2421
- Wer: 26.5185
- Cer: 9.4681
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: 32
- eval_batch_size: 32
- 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: 15000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.3717 | 0.35 | 1000 | 0.4004 | 46.9576 | 16.9664 |
| 0.286 | 0.69 | 2000 | 0.3129 | 37.3935 | 13.5504 |
| 0.2287 | 1.04 | 3000 | 0.2768 | 33.1931 | 11.7806 |
| 0.2257 | 1.39 | 4000 | 0.2590 | 30.7243 | 11.0232 |
| 0.2029 | 1.73 | 5000 | 0.2428 | 29.2003 | 10.4144 |
| 0.1691 | 2.08 | 6000 | 0.2408 | 28.4357 | 10.0306 |
| 0.1626 | 2.43 | 7000 | 0.2369 | 28.0588 | 10.0486 |
| 0.1588 | 2.77 | 8000 | 0.2321 | 27.2340 | 9.6819 |
| 0.1271 | 3.12 | 9000 | 0.2349 | 26.8407 | 9.5574 |
| 0.1263 | 3.47 | 10000 | 0.2356 | 27.1630 | 9.6519 |
| 0.1314 | 3.81 | 11000 | 0.2340 | 26.5567 | 9.4278 |
| 0.1062 | 4.16 | 12000 | 0.2390 | 26.6332 | 9.5162 |
| 0.1081 | 4.5 | 13000 | 0.2398 | 26.5840 | 9.5085 |
| 0.1033 | 4.85 | 14000 | 0.2402 | 26.7096 | 9.4801 |
| 0.097 | 5.2 | 15000 | 0.2421 | 26.5185 | 9.4681 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2