openai/whisper-large-v2
This model is a fine-tuned version of openai/whisper-large-v2 on the vumichien/preprocessed_jsut_jsss_css10_common_voice_11 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2284
- Wer: 7.6453
- Cer: 4.7187
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 |
|---|---|---|---|---|---|
| 0.1912 | 0.55 | 1000 | 0.1828 | 11.2314 | 7.0357 |
| 0.1329 | 1.1 | 2000 | 0.1618 | 9.4172 | 5.9028 |
| 0.0912 | 1.65 | 3000 | 0.1616 | 8.9257 | 5.4711 |
| 0.0576 | 2.2 | 4000 | 0.1664 | 8.5861 | 5.3055 |
| 0.0449 | 2.74 | 5000 | 0.1642 | 8.4510 | 5.2930 |
| 0.02 | 3.29 | 6000 | 0.1799 | 8.1537 | 5.0354 |
| 0.019 | 3.84 | 7000 | 0.1801 | 8.125 | 5.0827 |
| 0.0067 | 4.39 | 8000 | 0.2003 | 7.8412 | 4.8133 |
| 0.006 | 4.94 | 9000 | 0.2071 | 7.5811 | 4.7023 |
| 0.0022 | 5.49 | 10000 | 0.2284 | 7.6453 | 4.7187 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2