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README.md

@@ -56,14 +56,16 @@ This model fine-tunes **allenai/scibert_scivocab_uncased** across **307 ASJC sub
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 ## 📈 Metrics
-| Input Features                    | Labels | Precision | Recall | F1-Score |
-|-----------------------------------|--------|-----------|--------|----------|
-| Title + Container Title + Abstract| 307    | 0.912     | 0.885  | 0.892    |
-| Title + Abstract                  | 307    | 0.607     | 0.503  | 0.532    |
-| Title + Container Title           | 307    | 0.949     | 0.957  | 0.952    |
-| Title only                        | 307    | 0.528     | 0.416  | 0.448    |
-
-For **26 parent subjects**, F1-score improves to **0.934** with full metadata and to **0.694** with Title + Abstract.
+| Input Features                    | Labels | Precision | Recall | F1-Score (weighted) |
+|-----------------------------------|--------|-----------|--------|---------------------|
+| Title + Container Title + Abstract| 307    | 0.912     | 0.885  | 0.892               |
+| Title + Abstract                  | 307    | 0.607     | 0.503  | 0.532               |
+| Title + Container Title           | 307    | 0.949     | 0.957  | 0.952               |
+| Title only                        | 307    | 0.528     | 0.416  | 0.448               |
+
+For **26 parent subjects**, weighted F1-score improves to **0.934** using full metadata (Title + Container Title + Abstract) and **0.694** using Title + Abstract. 
+
+The evaluation dataset is publicly available: [github](https://github.com/grano94/ASJC-Classifier?tab=readme-ov-file).
 
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