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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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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- fleurs
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metrics:
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- wer
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model-index:
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- name: Whisper Small Ko(FLUERS) - by p4b
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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: FLUERS Korean
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type: fleurs
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config: ko_kr
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split: validation
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args: ko_kr
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metrics:
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- name: Wer
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type: wer
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value: 148.1005085252767
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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(FLUERS) - by p4b
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the FLUERS Korean dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4512
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- Wer: 148.1005
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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-07
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- train_batch_size: 96
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- eval_batch_size: 64
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- seed: 42
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- distributed_type: multi-GPU
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 500
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- training_steps: 4000
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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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| 0.6003 | 32.0 | 800 | 0.5913 | 167.2749 |
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| 0.459 | 64.0 | 1600 | 0.4978 | 170.9841 |
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| 0.4035 | 96.0 | 2400 | 0.4653 | 168.5911 |
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| 0.3812 | 128.0 | 3200 | 0.4531 | 149.4765 |
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| 0.3766 | 160.0 | 4000 | 0.4512 | 148.1005 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.14.0.dev20221208+cu116
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- Datasets 2.7.1.dev0
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- Tokenizers 0.13.2
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