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--- |
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language: |
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- ko |
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license: apache-2.0 |
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base_model: openai/whisper-base |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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model-index: |
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- name: whisper_finetune |
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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_finetune |
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the aihub_20000 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4938 |
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- Cer: 14.1359 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 4000 |
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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 | Cer | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:| |
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| 0.3736 | 0.8 | 500 | 0.4641 | 15.1146 | |
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| 0.2685 | 1.6 | 1000 | 0.4525 | 14.3150 | |
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| 0.1929 | 2.4 | 1500 | 0.4424 | 14.0470 | |
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| 0.1241 | 3.2 | 2000 | 0.4584 | 13.8724 | |
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| 0.1347 | 4.0 | 2500 | 0.4554 | 13.9110 | |
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| 0.0944 | 4.8 | 3000 | 0.4693 | 14.0391 | |
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| 0.0761 | 5.6 | 3500 | 0.4851 | 14.1281 | |
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| 0.0606 | 6.4 | 4000 | 0.4938 | 14.1359 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
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