leenag/Malasar_Medium
This model is a fine-tuned version of openai/whisper-medium on the Spoken Bible Corpus: Malasar dataset. It achieves the following results on the evaluation set:
- Loss: 0.5907
- Wer: 50.2570
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 |
|---|---|---|---|---|
| 0.0646 | 11.3636 | 250 | 0.3369 | 55.6254 |
| 0.0104 | 22.7273 | 500 | 0.4445 | 52.3130 |
| 0.0012 | 34.0909 | 750 | 0.4890 | 50.1428 |
| 0.0002 | 45.4545 | 1000 | 0.5240 | 50.3712 |
| 0.0002 | 56.8182 | 1250 | 0.5488 | 50.1999 |
| 0.0001 | 68.1818 | 1500 | 0.5695 | 50.3712 |
| 0.0001 | 79.5455 | 1750 | 0.5844 | 50.1999 |
| 0.0001 | 90.9091 | 2000 | 0.5907 | 50.2570 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.0
- Tokenizers 0.19.1
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Base model
openai/whisper-medium