whisper-tiny-mn-9
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3885
- Wer: 45.5102
- Cer: 17.3377
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: 64
- eval_batch_size: 64
- 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: 20000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.587 | 0.69 | 1000 | 0.6937 | 75.6336 | 29.6764 |
| 0.4536 | 1.39 | 2000 | 0.5539 | 64.8187 | 24.8324 |
| 0.3798 | 2.08 | 3000 | 0.4963 | 57.7944 | 22.1842 |
| 0.3423 | 2.77 | 4000 | 0.4661 | 54.3751 | 20.9705 |
| 0.3122 | 3.47 | 5000 | 0.4449 | 52.5945 | 20.3405 |
| 0.3002 | 4.16 | 6000 | 0.4285 | 50.5080 | 19.3499 |
| 0.2842 | 4.85 | 7000 | 0.4171 | 49.3937 | 19.0282 |
| 0.2655 | 5.54 | 8000 | 0.4099 | 48.6727 | 18.6045 |
| 0.2555 | 6.24 | 9000 | 0.4035 | 48.2084 | 18.3392 |
| 0.2525 | 6.93 | 10000 | 0.3990 | 47.3290 | 17.8338 |
| 0.243 | 7.62 | 11000 | 0.3963 | 47.0559 | 18.2524 |
| 0.2358 | 8.32 | 12000 | 0.3948 | 46.7337 | 17.8186 |
| 0.2288 | 9.01 | 13000 | 0.3901 | 46.5480 | 17.9172 |
| 0.2171 | 9.7 | 14000 | 0.3910 | 46.0236 | 17.6266 |
| 0.2184 | 10.4 | 15000 | 0.3904 | 46.4387 | 17.8228 |
| 0.2099 | 11.09 | 16000 | 0.3893 | 45.9744 | 17.4379 |
| 0.216 | 11.78 | 17000 | 0.3889 | 45.6194 | 17.2939 |
| 0.2095 | 12.47 | 18000 | 0.3895 | 45.7887 | 17.4438 |
| 0.2056 | 13.17 | 19000 | 0.3882 | 45.6085 | 17.2888 |
| 0.2064 | 13.86 | 20000 | 0.3885 | 45.5102 | 17.3377 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2