update model card README.md

README.md

@@ -4,9 +4,26 @@ tags:
 - generated_from_trainer
 datasets:
 - health_fact
+metrics:
+- accuracy
+- f1
 model-index:
 - name: distilbert-base-uncased-finetuned-health_facts
-  results: []
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: health_fact
+      type: health_fact
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6705107084019769
+    - name: F1
+      type: f1
+      value: 0.6201718138565402
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -15,6 +32,10 @@ should probably proofread and complete it, then remove this comment. -->
 # distilbert-base-uncased-finetuned-health_facts
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the health_fact dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7692
+- Accuracy: 0.6705
+- F1: 0.6202
 
 ## Model description
 
@@ -41,6 +62,14 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.8979        | 1.0   | 154  | 0.7750          | 0.6590   | 0.6126 |
+| 0.7806        | 2.0   | 308  | 0.7692          | 0.6705   | 0.6202 |
+
+
 ### Framework versions
 
 - Transformers 4.11.3