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: 0.4664
- Wer: 33.9911
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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.898 | 0.1 | 100 | 0.8296 | 53.0885 |
| 0.5673 | 0.2 | 200 | 0.6036 | 41.1596 |
| 0.5163 | 0.3 | 300 | 0.5389 | 38.9718 |
| 0.4647 | 1.084 | 400 | 0.5052 | 36.3355 |
| 0.4073 | 1.184 | 500 | 0.4919 | 35.4310 |
| 0.3885 | 1.284 | 600 | 0.4835 | 35.1604 |
| 0.3824 | 2.068 | 700 | 0.4720 | 34.1206 |
| 0.3513 | 2.168 | 800 | 0.4709 | 34.6946 |
| 0.3521 | 2.268 | 900 | 0.4675 | 34.4240 |
| 0.335 | 3.052 | 1000 | 0.4664 | 33.9911 |
Framework versions
- Transformers 4.52.0
- Pytorch 2.8.0+cu128
- Datasets 3.6.0
- Tokenizers 0.21.4