openai/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the vumichien/preprocessed_jsut_jsss_css10_common_voice_11 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2836
- Wer: 8.7213
- Cer: 5.4698
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: 32
- eval_batch_size: 16
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.1106 | 1.1 | 1000 | 0.1827 | 10.3480 | 6.4784 |
| 0.0487 | 2.2 | 2000 | 0.1799 | 9.4764 | 5.9127 |
| 0.0243 | 3.29 | 3000 | 0.1950 | 9.2111 | 5.8069 |
| 0.0106 | 4.39 | 4000 | 0.2113 | 8.9713 | 5.5756 |
| 0.0054 | 5.49 | 5000 | 0.2325 | 8.6470 | 5.4041 |
| 0.0031 | 6.59 | 6000 | 0.2462 | 8.7078 | 5.4409 |
| 0.0014 | 7.68 | 7000 | 0.2608 | 8.7145 | 5.4849 |
| 0.0009 | 8.78 | 8000 | 0.2695 | 8.6301 | 5.3876 |
| 0.0004 | 9.88 | 9000 | 0.2794 | 8.6064 | 5.3528 |
| 0.0003 | 10.98 | 10000 | 0.2836 | 8.7213 | 5.4698 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2