Whisper Small Hausa Fine-Tuned
This model is a fine-tuned version of openai/whisper-small on the Publica AI Hausa Dataset (184 hours) dataset. It achieves the following results on the evaluation set:
- Loss: 0.1969
- Wer: 9.1731
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1644 | 3.0183 | 1000 | 0.2328 | 13.9821 |
| 0.0645 | 7.0092 | 2000 | 0.2068 | 12.2836 |
| 0.0665 | 4.8940 | 3000 | 0.1559 | 8.5712 |
| 0.0073 | 6.5253 | 4000 | 0.1765 | 8.9126 |
| 0.0013 | 8.1566 | 5000 | 0.1907 | 8.7752 |
| 0.0008 | 9.7879 | 6000 | 0.1969 | 9.1731 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.20.3