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--- |
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library_name: transformers |
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language: |
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- ko |
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license: mit |
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base_model: openai/whisper-large-v3-turbo |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper Small ko |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Whisper Small ko |
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This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the custom dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0021 |
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- Wer: 0.2425 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 4e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 100 |
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- training_steps: 500 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:------:|:----:|:---------------:|:-------:| |
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| 0.0336 | 1.4706 | 100 | 0.1071 | 12.0453 | |
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| 0.0207 | 2.9412 | 200 | 0.0394 | 5.6589 | |
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| 0.0073 | 4.4118 | 300 | 0.0257 | 2.8294 | |
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| 0.0038 | 5.8824 | 400 | 0.0066 | 0.8892 | |
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| 0.0008 | 7.3529 | 500 | 0.0021 | 0.2425 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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