Update README.md

README.md

@@ -3,29 +3,27 @@ license: apache-2.0
 library_name: transformers
 pipeline_tag: text-classification
 tags:
-  - scibert
-  - data-paper-classification
-  - scholarly-papers
-  - binary-classification
+- scibert
+- data-paper-classification
+- scholarly-papers
+- binary-classification
 base_model: allenai/scibert_scivocab_uncased
-datasets:
-  - custom
 metrics:
-  - accuracy
-  - f1
+- accuracy
+- f1
 model-index:
-  - name: scibert-data-paper
-    results:
-      - task:
-          type: text-classification
-          name: Data Paper Classification
-        metrics:
-          - name: Edge Case Accuracy
-            type: accuracy
-            value: 1.0
-          - name: Mean Confidence
-            type: accuracy
-            value: 0.94
+- name: scibert-data-paper
+  results:
+  - task:
+      type: text-classification
+      name: Data Paper Classification
+    metrics:
+    - name: Edge Case Accuracy
+      type: accuracy
+      value: 1
+    - name: Mean Confidence
+      type: accuracy
+      value: 0.94
 ---
 
 # SciBERT Data-Paper Classifier
@@ -56,8 +54,12 @@ result = clf("MIMIC-III, a freely accessible critical care database")
 | Output | Binary: `data_paper` (1) / `not_data_paper` (0) |
 | Inference | CPU (no GPU required) |
 
+
+
 ## Training
 
+[Train Data](https://www.kaggle.com/datasets/zehrakorkusuz/labeling-4k-datasets-with-gemini-flash-2-0)
+
 Two-phase continued fine-tuning:
 
 1. **Phase 1**: 5 epochs, learning rate 2e-5
@@ -102,4 +104,4 @@ Concatenated `title + abstract`, truncated to 512 tokens. The model works well w
   year={2026},
   url={https://huggingface.co/zehralx/scibert-data-paper}
 }
-```
+```