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README.md
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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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library_name: peft
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tags:
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- generated_from_trainer
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base_model: openai/whisper-large-v2
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datasets:
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- customd_ataset
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model-index:
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- name: Whisper large-v2 Korean - ML_project_custom_data_3epoch_with500_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 large-v2 Korean - ML_project_custom_data_3epoch_with500_ko
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the customd_ataset dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6315
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- Cer: 102.3375
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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: 0.001
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- train_batch_size: 4
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- eval_batch_size: 2
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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: 50
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- num_epochs: 3
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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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| 0.3587 | 1.0 | 113 | 0.6581 | 75.6026 |
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| 0.2044 | 2.0 | 226 | 0.6616 | 87.1439 |
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| 0.0757 | 3.0 | 339 | 0.6315 | 102.3375 |
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### Framework versions
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- PEFT 0.11.2.dev0
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- Transformers 4.41.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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