Whisper Small SerendepifyLabs Twi ASR
This model is a fine-tuned version of openai/whisper-small on the WaxalNLP aka_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.4755
- Wer: 34.2849
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- 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: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.6845 | 0.1 | 200 | 0.6603 | 44.2810 |
| 0.4908 | 1.042 | 400 | 0.5130 | 37.1241 |
| 0.4007 | 1.142 | 600 | 0.4811 | 34.9633 |
| 0.3474 | 2.084 | 800 | 0.4633 | 34.6444 |
| 0.3016 | 3.026 | 1000 | 0.4581 | 34.0858 |
| 0.2758 | 3.126 | 1200 | 0.4647 | 34.7391 |
| 0.242 | 4.068 | 1400 | 0.4663 | 34.1438 |
| 0.2211 | 5.01 | 1600 | 0.4726 | 35.0309 |
| 0.1916 | 5.11 | 1800 | 0.4766 | 34.0607 |
| 0.1989 | 6.052 | 2000 | 0.4755 | 34.2849 |
Framework versions
- Transformers 4.52.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4