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whisper-kaggle-be3
This model is a fine-tuned version of openai/whisper-small on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3213
- Wer: 45.6094
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: 500
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0749 | 3.15 | 1000 | 0.1886 | 50.9273 |
| 0.0117 | 6.31 | 2000 | 0.2440 | 47.2937 |
| 0.0014 | 9.46 | 3000 | 0.2978 | 45.8933 |
| 0.0003 | 12.62 | 4000 | 0.3213 | 45.6094 |
Framework versions
- Transformers 4.33.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.4.dev0
- Tokenizers 0.13.3
