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update model card README.md
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README.md
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---
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language:
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- kr
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license: apache-2.0
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base_model: openai/whisper-large-v2
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tags:
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- generated_from_trainer
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datasets:
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- Jungwonchang/ksponspeech
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metrics:
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- wer
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model-index:
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- name: Whisper large-v2, KsponSpeech
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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: KsponSpeech
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type: Jungwonchang/ksponspeech
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config: dev
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split: validation
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args: dev
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metrics:
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- name: Wer
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type: wer
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value: 42.225687000584685
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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, KsponSpeech
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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 KsponSpeech dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2946
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- Wer: 42.2257
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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: 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: 50
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- training_steps: 2000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.3315 | 0.25 | 500 | 0.3446 | 41.5319 |
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| 0.3204 | 0.5 | 1000 | 0.3229 | 37.7003 |
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| 0.2967 | 0.75 | 1500 | 0.3054 | 38.3980 |
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| 0.2859 | 1.0 | 2000 | 0.2946 | 42.2257 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 1.12.1+cu116
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- Datasets 2.14.0
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- Tokenizers 0.12.1
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