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# whisper-large-v3-japanese-4k-steps
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4057
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- Wer: 1821.4909
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# whisper-large-v3-japanese-4k-steps
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the Common Voice 16.1 dataset. I followed a post by Sanchit Gandhi, https://huggingface.co/blog/fine-tune-whisper
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It took 24 hours using an A100 on Google Colab to complete 4000 steps using the Common Voice 16.1 dataset. Training loss dropped over epochs but WER increased suggesting overfitting. It achieves the following results on the evaluation set:
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- Loss: 0.4057
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- Wer: 1821.4909
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