Whisper Small for Hre - NT Viet
This model is a fine-tuned version of openai/whisper-small on the Hre audio dataset 3 dataset. It achieves the following results on the evaluation set:
- Loss: 1.2846
- Wer Ortho: 60.4439
- Wer: 50.9103
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
0.0416 | 5.32 | 500 | 1.2846 | 60.4439 | 50.9103 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for ntviet/whisper-small-hre3
Base model
openai/whisper-smallEvaluation results
- Wer on Hre audio dataset 3test set self-reported50.910