Whisper-med-eng - Log-english
This model is a fine-tuned version of openai/whisper-medium on the asr-tamil-cleaned dataset. It achieves the following results on the evaluation set:
- Loss: 0.1642
- Wer Ortho: 36.6838
- Wer: 10.3984
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
- 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 |
|---|---|---|---|---|---|
| 0.1613 | 0.0143 | 500 | 0.1642 | 36.6838 | 10.3984 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Logii33/whisper-medium-english
Base model
openai/whisper-mediumDataset used to train Logii33/whisper-medium-english
Evaluation results
- Wer on asr-tamil-cleanedself-reported10.398