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whisper-small-r22-e
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: 0.2918
- Wer: 21.3875
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: 16
- 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: 5
- training_steps: 150
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3822 | 0.09 | 10 | 0.4255 | 23.2826 |
| 0.2636 | 0.18 | 20 | 0.3321 | 22.4196 |
| 0.2037 | 0.27 | 30 | 0.3279 | 23.8071 |
| 0.1943 | 0.36 | 40 | 0.3177 | 22.3858 |
| 0.2203 | 0.45 | 50 | 0.3109 | 22.4873 |
| 0.193 | 0.54 | 60 | 0.3071 | 22.9272 |
| 0.2096 | 0.63 | 70 | 0.2990 | 22.6565 |
| 0.214 | 0.72 | 80 | 0.3029 | 22.4873 |
| 0.2375 | 0.81 | 90 | 0.2927 | 21.7259 |
| 0.2238 | 0.9 | 100 | 0.2918 | 22.4196 |
| 0.2119 | 0.99 | 110 | 0.2919 | 22.7580 |
| 0.1362 | 1.08 | 120 | 0.2897 | 22.0135 |
| 0.0997 | 1.17 | 130 | 0.2915 | 21.3029 |
| 0.0824 | 1.26 | 140 | 0.2920 | 21.4382 |
| 0.0923 | 1.35 | 150 | 0.2918 | 21.3875 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7.dev0
- Tokenizers 0.14.1
