openai/whisper-large-v2
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: 0.2352
- Wer: 8.1166
- Cer: 5.0032
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
- gradient_accumulation_steps: 2
- 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: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.0897 | 0.1 | 1000 | 0.1884 | 11.0068 | 6.6992 |
| 0.0396 | 0.2 | 2000 | 0.1749 | 9.7399 | 5.9350 |
| 0.036 | 1.1 | 3000 | 0.1698 | 9.1419 | 5.6781 |
| 0.012 | 1.2 | 4000 | 0.1849 | 9.3041 | 5.7661 |
| 0.0151 | 2.09 | 5000 | 0.1879 | 9.1959 | 5.6761 |
| 0.0047 | 2.19 | 6000 | 0.2097 | 8.6706 | 5.4422 |
| 0.0046 | 3.09 | 7000 | 0.2040 | 8.8277 | 5.4717 |
| 0.0015 | 3.19 | 8000 | 0.2260 | 8.4949 | 5.3101 |
| 0.0013 | 4.09 | 9000 | 0.2339 | 8.3716 | 5.1471 |
| 0.0005 | 4.19 | 10000 | 0.2352 | 8.1166 | 5.0032 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2