Whisper_Korean_fine-tune
This model is a fine-tuned version of openai/whisper-base on the TARARARAK/KsponSpeech_01_ALHUB_preprocess dataset. It achieves the following results on the evaluation set:
- Loss: 0.4357
- Cer: 14.3015
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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 0.5007 | 0.2690 | 1000 | 0.5043 | 17.1656 |
| 0.4516 | 0.5381 | 2000 | 0.4650 | 15.5761 |
| 0.4293 | 0.8071 | 3000 | 0.4440 | 14.9569 |
| 0.3653 | 1.0761 | 4000 | 0.4357 | 14.3015 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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Base model
openai/whisper-base