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README.md

@@ -1,36 +1,36 @@
 ---
 language:
-- en
+  - en
 license: apache-2.0
 base_model: emilyalsentzer/Bio_ClinicalBERT
 tags:
-- medical
-- clinical
-- ssi
-- classification
-- surveillance
+  - medical
+  - clinical
+  - ssi
+  - classification
+  - surveillance
 metrics:
-- accuracy
-- f1
-- precision
-- recall
+  - accuracy
+  - f1
+  - precision
+  - recall
 model-index:
-- name: clinicalSSIBERT
-  results:
-  - task:
-      type: text-classification
-      name: SSI Detection
-    dataset:
-      name: Synthetic UK NHS Clinical Notes
-      type: synthetic
-      split: test
-    metrics:
-    - type: accuracy
-      value: 1.0
-      name: Accuracy
-    - type: f1
-      value: 1.0
-      name: F1
+  - name: clinicalSSIBERT
+    results:
+      - task:
+          type: text-classification
+          name: SSI Detection
+        dataset:
+          name: Synthetic UK NHS Clinical Notes
+          type: synthetic
+          split: test
+        metrics:
+          - name: Accuracy
+            type: accuracy
+            value: 1.0
+          - name: F1
+            type: f1
+            value: 1.0
 ---
 
 # Model Card for Ch3DS/clinicalSSIBERT
@@ -99,25 +99,25 @@ print(f"Prediction: {labels[predicted_class_id]}")
 
 ### Training Data
 
-The model was trained on **1 million synthetic clinical notes** generated to mimic UK NHS postoperative records. The data covers:
+The model was trained on **5 million synthetic clinical notes** generated to mimic UK NHS postoperative records. The data covers:
 
 - **Procedures**: Total Hip/Knee Replacement, C-Section, Cholecystectomy, Hernia Repair, etc.
 - **Terminology**: UK-specific staff titles (Reg, SHO, FY1), antibiotics (Co-amoxiclav, Teicoplanin), and wound descriptions.
-- **Balance**: Approximately 15% infection rate.
+- **Balance**: Approximately 5% infection rate.
 
 ### Training Procedure
 
 #### Training Hyperparameters
 
 - **Epochs**: 3
-- **Batch Size**: 8 (per device) with Gradient Accumulation of 4 (Effective Batch Size: 32)
+- **Batch Size**: 64 (per device) with Gradient Accumulation of 4
 - **Learning Rate**: 2e-5
 - **Precision**: Mixed Precision (FP16)
 - **Optimizer**: AdamW
 
 #### Hardware
 
-- **GPU**: NVIDIA GeForce RTX 4050 Laptop GPU (6GB VRAM)
+- **GPU**: NVIDIA GeForce RTX 5070 Ti
 
 ## Evaluation
 
@@ -138,7 +138,7 @@ _Note: The perfect scores reflect the synthetic nature of the test data, which f
 
 ## Environmental Impact
 
-- **Hardware Type**: NVIDIA GeForce RTX 4050 Laptop GPU
+- **Hardware Type**: NVIDIA GeForce RTX 5070 Ti
 - **Hours used**: ~2 hours
 - **Carbon Emitted**: Negligible (local training)