leenag/Malasar_Luke
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: 0.5075
- Wer: 48.2010
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 |
|---|---|---|---|---|
| 0.018 | 11.3636 | 250 | 0.3526 | 50.2570 |
| 0.0059 | 22.7273 | 500 | 0.4000 | 49.5146 |
| 0.0002 | 34.0909 | 750 | 0.4418 | 48.3152 |
| 0.0001 | 45.4545 | 1000 | 0.4785 | 48.0868 |
| 0.0 | 56.8182 | 1250 | 0.4923 | 47.8013 |
| 0.0 | 68.1818 | 1500 | 0.5008 | 47.8013 |
| 0.0 | 79.5455 | 1750 | 0.5059 | 48.2010 |
| 0.0 | 90.9091 | 2000 | 0.5075 | 48.2010 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.0
- Tokenizers 0.19.1
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