Whisper Base Bengali
This model is a fine-tuned version of arun100/whisper-base-bn-6 on the mozilla-foundation/common_voice_16_0 bn dataset. It achieves the following results on the evaluation set:
- Loss: 0.2028
- Wer: 27.7210
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: 5e-07
- 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: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1388 | 1.72 | 500 | 0.2076 | 28.8529 |
| 0.1335 | 3.43 | 1000 | 0.2068 | 28.6171 |
| 0.1297 | 5.15 | 1500 | 0.2061 | 28.4462 |
| 0.13 | 6.86 | 2000 | 0.2050 | 28.4274 |
| 0.126 | 8.58 | 2500 | 0.2046 | 28.3500 |
| 0.122 | 10.29 | 3000 | 0.2044 | 28.1872 |
| 0.1205 | 12.01 | 3500 | 0.2039 | 28.1715 |
| 0.1187 | 13.72 | 4000 | 0.2038 | 28.0136 |
| 0.1152 | 15.44 | 4500 | 0.2035 | 28.0503 |
| 0.1133 | 17.15 | 5000 | 0.2035 | 28.0395 |
| 0.1167 | 18.87 | 5500 | 0.2031 | 27.9071 |
| 0.1119 | 20.58 | 6000 | 0.2032 | 27.8288 |
| 0.1168 | 22.3 | 6500 | 0.2030 | 27.8306 |
| 0.1129 | 24.01 | 7000 | 0.2029 | 27.7778 |
| 0.112 | 25.73 | 7500 | 0.2030 | 27.7415 |
| 0.1105 | 27.44 | 8000 | 0.2030 | 27.7482 |
| 0.1114 | 29.16 | 8500 | 0.2028 | 27.7608 |
| 0.1102 | 30.87 | 9000 | 0.2029 | 27.7357 |
| 0.1115 | 32.59 | 9500 | 0.2028 | 27.7210 |
| 0.1083 | 34.31 | 10000 | 0.2028 | 27.7353 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0