whisper-small-korr
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: 0.3466
- Wer: 19.9610
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3119 | 0.69 | 100 | 0.3334 | 20.6884 |
| 0.1223 | 1.39 | 200 | 0.3179 | 21.4336 |
| 0.0757 | 2.08 | 300 | 0.3234 | 20.3158 |
| 0.0349 | 2.77 | 400 | 0.3329 | 20.8481 |
| 0.0172 | 3.47 | 500 | 0.3354 | 20.1916 |
| 0.0059 | 4.16 | 600 | 0.3357 | 19.7480 |
| 0.0057 | 4.85 | 700 | 0.3396 | 19.9965 |
| 0.0046 | 5.55 | 800 | 0.3417 | 19.7658 |
| 0.0025 | 6.24 | 900 | 0.3461 | 20.0497 |
| 0.0029 | 6.93 | 1000 | 0.3466 | 19.9610 |
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3