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README.md
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## Model description
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## Intended uses & limitations
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### Training results
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### Framework versions
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- Transformers 4.44.2
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## Model description
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This model is fine-tuned for classifying GitHub issues into four categories: New Feature, Improvement, Bug, and Task. The base model used is bert-large-uncased, and it has been trained on an open-source dataset of GitHub issues containing titles and descriptions. This model can efficiently predict the type of issue based on the input of the issue’s title and description.
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### Fine-Tuning Details
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- Base Model: bert-large-uncased
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- Fine-Tuning Dataset: GitHub Issues with labels mapped to four categories:
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- New Feature
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- Improvement
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- Bug
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- Task
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- Training Framework: Hugging Face Transformers, PyTorch
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- Training Setup: The model was fine-tuned using a batch size of 64 for a few epochs, with a learning rate of 2e-5.
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## Intended uses & limitations
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### Training results
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### Framework versions
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- Transformers 4.44.2
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