Whisper Small Luganda
This model is a fine-tuned version of openai/whisper-small on the Common Voice 15.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3827
- Wer: 40.4513
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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6718 | 0.1129 | 500 | 0.7164 | 66.9178 |
| 0.4723 | 0.2258 | 1000 | 0.5436 | 54.4267 |
| 0.4208 | 0.3388 | 1500 | 0.4769 | 49.0925 |
| 0.3881 | 0.4517 | 2000 | 0.4404 | 45.3112 |
| 0.3739 | 0.5646 | 2500 | 0.4167 | 43.9251 |
| 0.3387 | 0.6775 | 3000 | 0.3993 | 41.2913 |
| 0.3405 | 0.7904 | 3500 | 0.3886 | 41.2099 |
| 0.3089 | 0.9033 | 4000 | 0.3827 | 40.4513 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for mn720/english
Base model
openai/whisper-smallDataset used to train mn720/english
Evaluation results
- Wer on Common Voice 15.0validation set self-reported40.451