End of training
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README.md
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---
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datasets:
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- Jpep26/AfterProcessing
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language:
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- ko
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library_name: transformers
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license: apache-2.0
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tags:
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- hf-asr-leaderboard
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- generated_from_trainer
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model-index:
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- name: Test
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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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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the AfterProcessing dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9167
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- Cer: 0.
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Cer |
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| 2.9456 | 0.6410 | 50 | 2.6740 | 0.
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| 1.2153 | 1.9231 | 150 | 1.1410 | 0.
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### Framework versions
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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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- Jpep26/AfterProcessing
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metrics:
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- wer
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model-index:
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- name: Test
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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: AfterProcessing
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type: Jpep26/AfterProcessing
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args: 'config: ko, split: valid'
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metrics:
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- name: Wer
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type: wer
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value: 0.7099697885196374
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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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This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the AfterProcessing dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9167
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- Cer: 0.8260
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- Wer: 0.7100
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- Mean: 0.7680
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## Model description
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Cer | Wer | Mean |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
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| 2.9456 | 0.6410 | 50 | 2.6740 | 0.5793 | 0.8061 | 0.6927 |
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| 1.7821 | 1.2821 | 100 | 1.6827 | 0.4616 | 0.6556 | 0.5586 |
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| 1.2153 | 1.9231 | 150 | 1.1410 | 0.4211 | 0.6017 | 0.5114 |
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| 0.8637 | 2.5641 | 200 | 0.9167 | 0.8260 | 0.7100 | 0.7680 |
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### Framework versions
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model.safetensors
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