Whisper Base Bengali
This model is a fine-tuned version of arun100/whisper-base-bn on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:
- Loss: 0.2151
- Wer: 29.9236
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 8500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2476 | 1.72 | 500 | 0.2751 | 36.1695 |
| 0.2284 | 3.43 | 1000 | 0.2622 | 35.1668 |
| 0.213 | 5.15 | 1500 | 0.2524 | 34.2022 |
| 0.2048 | 6.86 | 2000 | 0.2447 | 33.5266 |
| 0.1948 | 8.58 | 2500 | 0.2382 | 32.7495 |
| 0.1852 | 10.29 | 3000 | 0.2334 | 32.2322 |
| 0.1789 | 12.01 | 3500 | 0.2295 | 31.7244 |
| 0.1738 | 13.72 | 4000 | 0.2260 | 31.2341 |
| 0.166 | 15.44 | 4500 | 0.2236 | 30.9562 |
| 0.1629 | 17.15 | 5000 | 0.2214 | 30.8171 |
| 0.1636 | 18.87 | 5500 | 0.2194 | 30.4368 |
| 0.1578 | 20.58 | 6000 | 0.2181 | 30.2520 |
| 0.1628 | 22.3 | 6500 | 0.2170 | 30.1858 |
| 0.1566 | 24.01 | 7000 | 0.2161 | 30.0694 |
| 0.1564 | 25.73 | 7500 | 0.2156 | 29.9943 |
| 0.1545 | 27.44 | 8000 | 0.2153 | 29.9294 |
| 0.1548 | 29.16 | 8500 | 0.2151 | 29.9236 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0