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# bert-base-uncased-issues-128
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the
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It achieves the following results on the evaluation set:
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- Loss: 1.2520
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# bert-base-uncased-issues-128
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the GitHub issues dataset. The model is used in Chapter 9: Dealing with Few to No Labels in the [NLP with Transformers book](https://learning.oreilly.com/library/view/natural-language-processing/9781098103231/). You can find the full code in the accompanying [Github repository](https://github.com/nlp-with-transformers/notebooks/blob/main/09_few-to-no-labels.ipynb).
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It achieves the following results on the evaluation set:
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- Loss: 1.2520
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