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README.md

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+
+---
+language: de
+license: mit
+library_name: transformers
+pipeline_tag: text-classification
+tags:
+- bibliographic-classification
+- bk-codes
+- german-libraries
+- multi-label-classification
+- bart
+datasets:
+- k10plus-catalog
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+- matthews_correlation
+---
+
+# BK Classification - Two-Stage BART
+
+This model performs automatic classification of German bibliographic records using BK (Basisklassifikation) codes.
+
+## Model Description
+
+This is a **two-stage fine-tuned BART-large model** for multi-label classification of bibliographic metadata into BK classification codes. The model achieved **state-of-the-art performance** on the K10plus library catalog dataset.
+
+### Performance
+
+- **Subset Accuracy**: 25.7%
+- **Matthews Correlation Coefficient (MCC)**: 0.498
+- **F1-Score (Micro)**: 47.9%
+- **F1-Score (Macro)**: 21.4%
+- **Precision (Micro)**: 66.1%
+- **Recall (Micro)**: 37.6%
+
+### Training Approach
+
+The model uses a **two-stage fine-tuning approach**:
+
+1. **Stage 1**: Train on parent BK categories (48 labels)
+2. **Stage 2**: Fine-tune on all BK codes (1,884 labels) using Stage 1 as initialization
+
+This approach outperformed both standard fine-tuning and hierarchical joint training.
+
+### Dataset
+
+- **Source**: K10plus German library catalog (2010-2020)
+- **Total Records**: 250,831 bibliographic entries
+- **Labels**: 1,884 unique BK classification codes
+- **Input Fields**: Title, Summary, Keywords, LOC Keywords, RVK codes
+
+### Usage
+
+```python
+import torch
+from transformers import AutoTokenizer
+from huggingface_hub import hf_hub_download
+
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained("mrehank209/bk-classification-bart-two-stage")
+
+# Load model components (see repository for full inference code)
+# This model requires custom loading due to the classifier head
+```
+
+### Citation
+
+If you use this model, please cite:
+
+```bibtex
+@misc{bk-classification-bart,
+  title={Automatic BK Classification using Two-Stage BART Fine-tuning},
+  author={Khalid, M. Rehan},
+  year={2025},
+  howpublished={Hugging Face Model Hub},
+  url={https://huggingface.co/mrehank209/bk-classification-bart-two-stage}
+}
+```
+
+### Contact
+
+- **Author**: M. Rehan Khalid
+- **Email**: m.khalid@stud.uni-goettingen.de
+- **Affiliation**: University of Göttingen
+
+### License
+
+MIT License