Whisper Base Wolof
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2902
- Wer: 32.8385
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5632 | 1.14 | 1000 | 0.4672 | 48.8263 |
| 0.3464 | 2.29 | 2000 | 0.3461 | 34.6403 |
| 0.2514 | 3.43 | 3000 | 0.3013 | 32.1406 |
| 0.1957 | 4.57 | 4000 | 0.2902 | 32.8385 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.13.3
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Model tree for serge-wilson/whisper-base-wolof
Base model
openai/whisper-base