whisper-small-akan
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: 0.9537
- Wer: 35.7102
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: 0.0001
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0761 | 10.0 | 250 | 0.6787 | 41.9921 |
| 0.0557 | 20.0 | 500 | 0.7485 | 42.4731 |
| 0.0273 | 30.0 | 750 | 0.8616 | 40.3509 |
| 0.0123 | 40.0 | 1000 | 0.9085 | 38.3701 |
| 0.0024 | 50.0 | 1250 | 0.9378 | 36.7572 |
| 0.0002 | 60.0 | 1500 | 0.9400 | 36.5025 |
| 0.0001 | 70.0 | 1750 | 0.9507 | 35.9366 |
| 0.0001 | 80.0 | 2000 | 0.9537 | 35.7102 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small