whisper-small-afrispeech
This model is a fine-tuned version of openai/whisper-small on the AfriSpeech-200 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5951
- Wer Ortho: 20.5418
- Wer: 16.2611
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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.0475 | 6.0976 | 500 | 0.5951 | 20.5418 | 16.2611 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 2.18.0
- Tokenizers 0.22.1
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Model tree for naalamle/whisper-small-afrispeech
Base model
openai/whisper-small