Update README.md

README.md

@@ -19,38 +19,45 @@ model-index:
     metrics:
     - name: Macro F1
       type: f1
-      value: 0.666486375029903
-    - name: Micro F1
-      type: f1
-      value: 0.7939983779399836
-    - name: False F1
-      type: f1
-      value: 0.787128712871287
-    - name: Mixture F1
-      type: f1
-      value: 0.5117493472584855
-    - name: True F1
-      type: f1
-      value: 0.911371237458194
-    - name: Unproven F1
-      type: f1
-      value: 0.4556962025316456
+      value: 0.6694031411935434
+    - name: Accuracy
+      type: accuracy
+      value: 0.7948094079480941
+    - name: False Accuracy
+      type: accuracy
+      value: 0.8092783505154639
+    - name: Mixture Accuracy
+      type: accuracy
+      value: 0.4975124378109453
+    - name: True Accuracy
+      type: accuracy
+      value: 0.9148580968280468
+    - name: Unproven Accuracy
+      type: accuracy
+      value: 0.4
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+
 
 # bigbird-base-health-fact
 
 This model is a fine-tuned version of [google/bigbird-roberta-base](https://huggingface.co/google/bigbird-roberta-base) on the health_fact dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5864
-- Micro F1: 0.8130
-- Macro F1: 0.6874
-- False F1: 0.8114
-- Mixture F1: 0.4557
-- True F1: 0.9154
-- Unproven F1: 0.5672
+It achieves the following results on the VALIDATION set:
+- Overall Accuracy: 0.8228995057660626
+- Macro F1: 0.6979224830442152
+- False Accuracy: 0.8289473684210527
+- Mixture Accuracy: 0.47560975609756095
+- True Accuracy: 0.9332273449920508
+- Unproven Accuracy: 0.4634146341463415
+
+It achieves the following results on the TEST set:
+
+- Overall Accuracy: 0.7948094079480941
+- Macro F1: 0.6694031411935434
+- Mixture Accuracy: 0.4975124378109453
+- False Accuracy: 0.8092783505154639
+- True Accuracy: 0.9148580968280468
+- Unproven Accuracy: 0.4
 
 The metrics in the eval results on the right-side are for the TEST set. The above results are for the VALIDATION set.