whisper-large-el
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1895
- Wer: 8.9989
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: 8
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0987 | 0.2 | 1000 | 0.1966 | 13.6516 |
| 0.0772 | 0.4 | 2000 | 0.1812 | 12.2771 |
| 0.0398 | 0.6 | 3000 | 0.1734 | 11.3113 |
| 0.0775 | 0.8 | 4000 | 0.1699 | 9.7975 |
| 0.0314 | 1.0 | 5000 | 0.1895 | 8.9989 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2