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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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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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base_model: openai/whisper-large-v3 |
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metrics: |
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- wer |
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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-large-v3](https://huggingface.co/openai/whisper-large-v3) on the aihub_100000 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3754 |
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- Cer: 6.9474 |
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- Wer: 28.5714 |
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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-08 |
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- train_batch_size: 16 |
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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: 2000 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| |
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| 0.4274 | 0.14 | 1000 | 0.3982 | 6.9437 | 28.4443 | |
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| 0.3884 | 0.28 | 2000 | 0.3754 | 6.9474 | 28.5714 | |
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### Framework versions |
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- Transformers 4.39.0.dev0 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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