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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: 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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datasets:
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- hyk000/woerae
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model-index:
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- name: wr_md
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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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# wr_md
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the wr_ds dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0903
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- Cer: 9.2605
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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: 16
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- eval_batch_size: 8
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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: 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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| 0.0486 | 3.8462 | 1000 | 0.1159 | 7.9222 |
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| 0.0034 | 7.6923 | 2000 | 0.0927 | 11.2435 |
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| 0.0015 | 11.5385 | 3000 | 0.0906 | 10.8821 |
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| 0.0012 | 15.3846 | 4000 | 0.0903 | 9.2605 |
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### Framework versions
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- Transformers 4.47.0.dev0
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- Pytorch 2.5.0
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- Datasets 3.0.2
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- Tokenizers 0.20.1
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