Whisper Small Swahili
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 sw dataset. It achieves the following results on the evaluation set:
- Loss: 0.6442
- Wer: 23.7246
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: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2694 | 1.07 | 1000 | 0.5438 | 26.8354 |
| 0.2306 | 3.02 | 2000 | 0.5081 | 23.9231 |
| 0.0467 | 4.09 | 3000 | 0.5648 | 24.4085 |
| 0.0239 | 6.03 | 4000 | 0.5994 | 23.8634 |
| 0.0123 | 7.1 | 5000 | 0.6442 | 23.7246 |
Framework versions
- Transformers 4.30.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.1.dev0
- Tokenizers 0.13.3
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Dataset used to train alamsher/whisper-small-sw
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 swtest set self-reported23.725