End of training
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README.md
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---
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tags:
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: whisper_checkpoints
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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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# whisper_checkpoints
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This model
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It achieves the following results on the evaluation set:
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- Loss: 0.1501
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- Wer: 10.8568
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More information needed
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## How to use
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This model can be used with the `transformers` library as follows:
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```python
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from transformers import WhisperForConditionalGeneration, WhisperProcessor
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model = WhisperForConditionalGeneration.from_pretrained("tmtms/whisper_checkpoints")
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processor = WhisperProcessor.from_pretrained("tmtms/whisper_checkpoints")
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## Intended uses & limitations
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More information needed
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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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base_model: INo0121/whisper-base-ko-callvoice
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tags:
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- generated_from_trainer
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datasets:
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- kresnik/zeroth_korean
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metrics:
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- wer
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model-index:
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- name: whisper_checkpoints
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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: Zeroth-Korean
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type: kresnik/zeroth_korean
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args: 'config: ko, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 10.856798674898359
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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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# whisper_checkpoints
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This model is a fine-tuned version of [INo0121/whisper-base-ko-callvoice](https://huggingface.co/INo0121/whisper-base-ko-callvoice) on the Zeroth-Korean dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1501
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- Wer: 10.8568
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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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