Whisper Small Few Audios - vfranchis
This model is a fine-tuned version of openai/whisper-small on the Few audios 1.0 dataset. It achieves the following results on the evaluation set:
- Loss: 1.6364
- Wer: 66.6667
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: 10
- training_steps: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6824 | 2.8571 | 10 | 1.6364 | 66.6667 |
| 4.2687 | 5.7143 | 20 | 1.6364 | 66.6667 |
| 2.6441 | 8.5714 | 30 | 1.6364 | 66.6667 |
| 1.8789 | 11.4286 | 40 | 1.6364 | 66.6667 |
| 1.3406 | 14.2857 | 50 | 1.6364 | 66.6667 |
| 0.8864 | 17.1429 | 60 | 1.6364 | 66.6667 |
| 1.0665 | 20.0 | 70 | 1.6364 | 66.6667 |
| 0.5324 | 22.8571 | 80 | 1.6364 | 66.6667 |
| 4.0741 | 25.7143 | 90 | 1.6364 | 66.6667 |
| 2.8755 | 28.5714 | 100 | 1.6364 | 66.6667 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small