whisper-small-kamba-model
This model is a fine-tuned version of Musembi/whisper-small-kamba-model on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1528
- Wer: 76.92
- Cer: 25.02
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.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: 50
- training_steps: 400
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.8431 | 0.2439 | 50 | 1.2481 | 75.99 | 25.19 |
| 1.9287 | 0.4878 | 100 | 1.2040 | 80.08 | 26.06 |
| 1.8232 | 0.7317 | 150 | 1.1776 | 80.12 | 25.4 |
| 1.7154 | 0.9756 | 200 | 1.1629 | 79.87 | 25.98 |
| 1.5737 | 1.2195 | 250 | 1.1575 | 80.37 | 26.03 |
| 1.5427 | 1.4634 | 300 | 1.1532 | 81.0 | 26.61 |
| 1.5164 | 1.7073 | 350 | 1.1488 | 81.07 | 25.82 |
| 1.5292 | 1.9512 | 400 | 1.1476 | 81.76 | 26.18 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 2.21.0
- Tokenizers 0.22.2