Whisper Small Even - VovaK13
This model is a fine-tuned version of openai/whisper-small on the Even Speech Biblical dataset. It achieves the following results on the evaluation set:
- Loss: 0.4483
- Wer: 30.2757
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 250
- training_steps: 2500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0509 | 5.9880 | 500 | 0.3699 | 33.7343 |
0.0022 | 11.9760 | 1000 | 0.4084 | 30.9273 |
0.0003 | 17.9641 | 1500 | 0.4336 | 30.1253 |
0.0002 | 23.9521 | 2000 | 0.4444 | 30.2757 |
0.0002 | 29.9401 | 2500 | 0.4483 | 30.2757 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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