Whisper Base Bn - Raiyan Ahmed
This model is a fine-tuned version of openai/whisper-base on the Common Voice 16.1 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1074
- Wer: 33.4498
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: 3e-05
- train_batch_size: 26
- eval_batch_size: 46
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2369 | 0.6365 | 1000 | 0.2433 | 62.1881 |
| 0.1242 | 1.2731 | 2000 | 0.1734 | 49.4369 |
| 0.1022 | 1.9096 | 3000 | 0.1197 | 39.0531 |
| 0.046 | 2.5461 | 4000 | 0.1067 | 34.5497 |
| 0.0702 | 2.6247 | 5000 | 0.1210 | 38.4777 |
| 0.1028 | 1.5748 | 6000 | 0.1484 | 44.2750 |
| 0.0772 | 1.8373 | 7000 | 0.1323 | 40.2388 |
| 0.0648 | 2.0997 | 8000 | 0.1205 | 39.1165 |
| 0.0367 | 2.3622 | 9000 | 0.1154 | 35.6332 |
| 0.0249 | 2.6247 | 10000 | 0.1074 | 33.4498 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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