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README.md
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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-small
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tags:
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- generated_from_trainer
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datasets:
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- didiudom94/gentlemen
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metrics:
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- bleu
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model-index:
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- name: Whisper Small Ko to En
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Gentlemen
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type: didiudom94/gentlemen
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args: 'split: train'
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metrics:
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- name: Bleu
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type: bleu
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value: 0.1392438982977928
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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 Small Ko to En
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Gentlemen dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.3270
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- Bleu: 0.1392
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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: 8
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- eval_batch_size: 8
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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: 5000
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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 | Bleu |
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|:-------------:|:------:|:----:|:---------------:|:------:|
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| 0.8182 | 0.2253 | 1000 | 1.6561 | 0.1004 |
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| 1.4212 | 0.4507 | 2000 | 1.4204 | 0.1195 |
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| 1.3578 | 0.6760 | 3000 | 1.3638 | 0.1320 |
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| 1.3446 | 0.9013 | 4000 | 1.3265 | 0.1356 |
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| 0.9391 | 1.1266 | 5000 | 1.3270 | 0.1392 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.5.1+cu121
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- Datasets 3.2.0
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- Tokenizers 0.20.3
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