Whisper Medium TH - Custom datasets and Common voice 17
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1381
- Wer: 59.0037
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: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2596 | 0.2406 | 500 | 0.2345 | 75.1845 |
0.2048 | 0.4812 | 1000 | 0.1912 | 68.9176 |
0.164 | 0.7218 | 1500 | 0.1702 | 66.5990 |
0.1612 | 0.9625 | 2000 | 0.1496 | 61.9680 |
0.075 | 1.2031 | 2500 | 0.1438 | 59.8647 |
0.0835 | 1.4437 | 3000 | 0.1381 | 59.0037 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
openai/whisper-medium