Whisper Medium Indonesian for Disaster Response
This model is a fine-tuned version of openai/whisper-small on the Indonesian Speech Dataset (InaVoCript, Fleurs, OpenSLR Javanese) dataset. It achieves the following results on the evaluation set:
- Loss: 1.1027
- Wer: 26.5584
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2835 | 1.3966 | 500 | 0.6987 | 26.6883 |
| 0.1078 | 2.7933 | 1000 | 0.7034 | 27.4675 |
| 0.023 | 4.1899 | 1500 | 0.8593 | 26.1039 |
| 0.0096 | 5.5866 | 2000 | 0.9625 | 26.9481 |
| 0.0051 | 6.9832 | 2500 | 0.9902 | 26.4935 |
| 0.0022 | 8.3799 | 3000 | 1.0349 | 25.7143 |
| 0.0016 | 9.7765 | 3500 | 1.0602 | 28.7338 |
| 0.0013 | 11.1732 | 4000 | 1.0808 | 26.2662 |
| 0.0012 | 12.5698 | 4500 | 1.0928 | 28.1494 |
| 0.0011 | 13.9665 | 5000 | 1.1027 | 26.5584 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.8.0+cu129
- Datasets 3.0.1
- Tokenizers 0.20.0