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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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- jindol/debugged_03_Whisper_datasets
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model-index:
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- name: repo_name
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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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# repo_name
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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the debugged_03_Whisper_datasets dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6540
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- Cer: 32.5714
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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-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 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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| 0.0001 | 500.0 | 1000 | 1.4956 | 32.5714 |
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| 0.0001 | 1000.0 | 2000 | 1.5831 | 36.0 |
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| 0.0 | 1500.0 | 3000 | 1.6306 | 32.5714 |
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| 0.0 | 2000.0 | 4000 | 1.6540 | 32.5714 |
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### Framework versions
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- Transformers 4.46.2
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- Pytorch 2.0.1
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- Datasets 3.1.0
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- Tokenizers 0.20.3
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