Whisper whisper-large-v3 sot
This model is a fine-tuned version of openai/whisper-large-v3 on the dsfsi-anv/za-african-next-voices dataset. It achieves the following results on the evaluation set:
- Loss: 0.4477
- Wer: 22.0832
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 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.9876 | 0.2 | 200 | 0.7042 | 44.9886 |
| 0.3854 | 0.4 | 400 | 0.5672 | 28.1945 |
| 0.2921 | 0.6 | 600 | 0.5097 | 24.3182 |
| 0.7161 | 0.8 | 800 | 0.4786 | 27.4673 |
| 0.5566 | 1.0 | 1000 | 0.4477 | 22.0832 |
Framework versions
- Transformers 4.52.0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.4
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Model tree for sitwala/whisper-large-v3-anv-sot
Base model
openai/whisper-large-v3