Whisper Large Thai Combined - 1000iter
This model is a fine-tuned version of openai/whisper-large-v2 on the mozilla-foundation/common_voice_11_0 th dataset. It achieves the following results on the evaluation set:
- Loss: 0.1244
- Wer: 15.5103
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1845 | 1.05 | 5000 | 0.1244 | 15.5103 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1
- Tokenizers 0.13.2
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Dataset used to train biodatlab/whisper-th-large-combined
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 thtest set self-reported15.510