whisper-small-tonga_5hrs
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: 0.9145
- Wer: 52.2928
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.3353 | 1.45 | 200 | 1.9984 | 113.0627 |
| 1.7712 | 2.9 | 400 | 1.2576 | 72.0656 |
| 1.1476 | 4.35 | 600 | 1.0129 | 59.8233 |
| 1.004 | 5.79 | 800 | 0.9406 | 53.2183 |
| 0.9169 | 7.25 | 1000 | 0.9145 | 52.2928 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
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