leenag/Malasar_Dict
This model is a fine-tuned version of openai/whisper-small on the Spoken Bible Corpus: Malasar dataset. It achieves the following results on the evaluation set:
- Loss: 0.0139
- Wer: 7.6014
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: 16
- 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.042 | 0.6410 | 250 | 0.0392 | 18.1869 |
| 0.023 | 1.2821 | 500 | 0.0318 | 14.5833 |
| 0.0158 | 1.9231 | 750 | 0.0215 | 10.5293 |
| 0.0106 | 2.5641 | 1000 | 0.0175 | 11.5428 |
| 0.0035 | 3.2051 | 1250 | 0.0145 | 7.5450 |
| 0.0027 | 3.8462 | 1500 | 0.0139 | 9.1779 |
| 0.0018 | 4.4872 | 1750 | 0.0144 | 7.5450 |
| 0.0016 | 5.1282 | 2000 | 0.0139 | 7.6014 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.19.1