change f1 to accuracy. add test results

README.md

@@ -19,27 +19,27 @@ model-index:
     - name: Macro F1
       type: f1
       value: 0.6732897445517078
-    - name: Micro F1
-      type: f1
+    - name: Accuracy
+      type: accuracy
       value: 0.797242497972425
-    - name: False F1
+    - name: False Accuracy
       type: f1
-      value: 0.7889447236180904
-    - name: Mixture F1
+      value: 0.8092783505154639
+    - name: Mixture Accuracy
       type: f1
-      value: 0.535
-    - name: True F1
+      value: 0.5323383084577115
+    - name: True Accuracy
       type: f1
-      value: 0.9135180520570949
-    - name: Unproven F1
+      value: 0.9081803005008348
+    - name: Unproven Accuracy
       type: f1
-      value: 0.4556962025316456
+      value: 0.4
 ---
 
 # longformer-base-health-fact2
 
 This model is a fine-tuned version of [allenai/longformer-base-4096](https://huggingface.co/allenai/longformer-base-4096) on the health_fact dataset.
-It achieves the following results on the evaluation set:
+It achieves the following results on the VALIDATION set:
 - Loss: 0.5858
 - Micro F1: 0.8122
 - Macro F1: 0.6830
@@ -48,6 +48,13 @@ It achieves the following results on the evaluation set:
 - True F1: 0.9234
 - Unproven F1: 0.5128
 
+The following are the results on the TEST set:
+- Macro F1: 0.6732897445517078
+- Accuracy: 0.797242497972425
+- False Accuracy: 0.8092783505154639
+- Mixture Accuracy: 0.5323383084577115
+- True Accuracy: 0.9081803005008348
+- Unproven Accuracy: 0.4
 ## Model description
 
 The health fact dataset is for building fact-checking models related to health. Here is how you can use this model: