Whisper Small 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: 0.2947
- Wer: 11.3990
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1756 | 1.6920 | 1000 | 0.2161 | 13.1418 |
| 0.0286 | 3.3841 | 2000 | 0.2258 | 11.6502 |
| 0.0065 | 5.0761 | 3000 | 0.2446 | 11.6659 |
| 0.0032 | 6.7682 | 4000 | 0.2531 | 11.2420 |
| 0.0022 | 8.4602 | 5000 | 0.2674 | 11.2577 |
| 0.001 | 10.1523 | 6000 | 0.2728 | 11.3990 |
| 0.0006 | 11.8443 | 7000 | 0.2819 | 11.7287 |
| 0.0004 | 13.5364 | 8000 | 0.2877 | 11.6502 |
| 0.0003 | 15.2284 | 9000 | 0.2927 | 11.5560 |
| 0.0003 | 16.9205 | 10000 | 0.2947 | 11.3990 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.8.0+cu129
- Datasets 3.0.1
- Tokenizers 0.20.0