whisper-small-swahili
This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6821
- Wer: 34.9438
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3797 | 1.5625 | 1000 | 0.6029 | 40.2361 |
| 0.1129 | 3.125 | 2000 | 0.5886 | 35.5841 |
| 0.0507 | 4.6875 | 3000 | 0.6397 | 35.4404 |
| 0.0161 | 6.25 | 4000 | 0.6821 | 34.9438 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for NMutangana/whisper-small-swahili
Base model
openai/whisper-small