Epoch	Training Loss	Validation Loss	F1	ROC AUC	Accuracy
1	No log	0.1774	0.910	0.9368	0.766
2	0.0606	0.1849	0.921	0.9454	0.787
3	0.0351	0.2071	0.919	0.9434	0.787
4	0.0180	0.2191	0.921	0.9451	0.793
5	0.0093	0.2295	0.921	0.9451	0.793
6	0.0060	0.2307	0.921	0.9451	0.793

Best epoch: 6 (highest F1 and accuracy, last improvement at epoch 4)

Per-Category Classification Report

Base model: <a href="https://huggingface.co/allenai/specter2_base" target="_blank" rel="noopener noreferrer" class="text-blue-400 hover:text-blue-300 underline underline-offset-2 transition-colors">allenai/specter2_base
Task: Multilabel classification (assigns one or more clusters per document)
Labels: 6 Horizon Europe clusters (see below)
Languages: English
Input: Title and abstract concatenated

Label	Precision	Recall	F1-score	Support
Civil Security for Society	0.97	0.79	0.87	39
Climate, Energy and Mobility	0.94	0.91	0.93	91
Culture, Creativity and Inclusive Society	0.89	0.88	0.88	96
Digital, Industry and Space	0.93	0.92	0.93	214
Food, Bioeconomy, Natural Resources, Agriculture and Environment	0.89	0.97	0.93	75
Health	0.96	0.96	0.96	73
micro avg	0.93	0.91	0.92	588
macro avg	0.93	0.91	0.92	588
weighted avg	0.93	0.91	0.92	588
samples avg	0.91	0.92	0.90	588

License

This model is licensed under the Apache License 2.0.