Whisper Base Shona + Tshivenda - Cleaned Data
This model is a fine-tuned version of openai/whisper-base on the Cleaned WAXAL Shona + Swivuriso Tshivenda dataset. It achieves the following results on the evaluation set:
- Loss: 0.5899
- Wer: 48.7657
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: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.1846 | 0.0882 | 200 | 1.2058 | 79.2304 |
| 0.8066 | 0.1764 | 400 | 0.8677 | 65.0463 |
| 0.7158 | 0.2646 | 600 | 0.7538 | 57.1436 |
| 0.6391 | 0.3527 | 800 | 0.6928 | 55.1938 |
| 0.6140 | 0.4409 | 1000 | 0.6560 | 52.6030 |
| 0.5697 | 0.5291 | 1200 | 0.6290 | 51.2560 |
| 0.5357 | 0.6173 | 1400 | 0.6114 | 48.9857 |
| 0.5352 | 0.7055 | 1600 | 0.5992 | 48.9450 |
| 0.5247 | 0.7937 | 1800 | 0.5924 | 48.7657 |
| 0.5443 | 0.8818 | 2000 | 0.5899 | 48.7657 |
Framework versions
- Transformers 5.14.1
- Pytorch 2.13.0+cu130
- Datasets 5.0.1
- Tokenizers 0.22.2