Whisper Small
This model is a fine-tuned version of openai/whisper-small on the AfriVoice dataset. It achieves the following results on the evaluation set:
- Loss: 1.0151
- Wer: 37.2345
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: 16
- seed: 42
- gradient_accumulation_steps: 2
- 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: 40
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1977 | 8.1301 | 500 | 0.7429 | 41.9683 |
| 0.0059 | 16.2602 | 1000 | 0.9167 | 38.4064 |
| 0.001 | 24.3902 | 1500 | 0.9849 | 37.3501 |
| 0.0007 | 32.5203 | 2000 | 1.0151 | 37.2345 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-small