Whisper Medium Shona - Cleaned Data
This model is a fine-tuned version of openai/whisper-base on the Cleaned Google WAXAL Shona dataset. It achieves the following results on the evaluation set:
- Loss: 0.4745
- Wer: 38.1120
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: cosine
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6465 | 0.5995 | 500 | 0.6614 | 53.6187 |
| 0.4528 | 1.1990 | 1000 | 0.4979 | 43.8992 |
| 0.4046 | 1.7986 | 1500 | 0.4480 | 40.3579 |
| 0.3495 | 2.3981 | 2000 | 0.4258 | 39.6383 |
| 0.3408 | 2.9976 | 2500 | 0.4087 | 37.3055 |
| 0.2667 | 3.5971 | 3000 | 0.4093 | 37.1480 |
| 0.2196 | 4.1966 | 3500 | 0.4092 | 36.8628 |
| 0.2352 | 4.7962 | 4000 | 0.4058 | 36.4691 |
| 0.1896 | 5.3957 | 4500 | 0.4145 | 36.3957 |
| 0.1973 | 5.9952 | 5000 | 0.4187 | 36.4935 |
| 0.1476 | 6.5947 | 5500 | 0.4271 | 37.2213 |
| 0.1244 | 7.1942 | 6000 | 0.4409 | 37.1643 |
| 0.1299 | 7.7938 | 6500 | 0.4430 | 36.8112 |
| 0.1107 | 8.3933 | 7000 | 0.4558 | 37.7590 |
| 0.1183 | 8.9928 | 7500 | 0.4572 | 37.9464 |
| 0.0944 | 9.5923 | 8000 | 0.4676 | 37.7400 |
| 0.0884 | 10.1918 | 8500 | 0.4707 | 37.9464 |
| 0.0873 | 10.7914 | 9000 | 0.4725 | 38.0605 |
| 0.0843 | 11.3909 | 9500 | 0.4742 | 38.0360 |
| 0.0836 | 11.9904 | 10000 | 0.4745 | 38.1120 |
Framework versions
- Transformers 5.14.1
- Pytorch 2.13.0+cu130
- Datasets 5.0.1
- Tokenizers 0.22.2