Whisper Small En - Moh
This model is a fine-tuned version of openai/whisper-small on the AfriSpeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.6236
- Wer: 32.8714
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.677 | 0.5 | 500 | 0.6841 | 31.2466 |
| 0.428 | 1.0 | 1000 | 0.6236 | 32.8714 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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Dataset used to train MohDz/dsn_afrispeech_small
Evaluation results
- Wer on AfriSpeechself-reported32.871