update model card README.md

README.md

@@ -3,9 +3,36 @@ tags:
 - generated_from_trainer
 datasets:
 - klue
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: ko_roberta_small_model
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: klue
+      type: klue
+      config: ner
+      split: validation
+      args: ner
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.6827303934512807
+    - name: Recall
+      type: recall
+      value: 0.7253980500806622
+    - name: F1
+      type: f1
+      value: 0.703417786090801
+    - name: Accuracy
+      type: accuracy
+      value: 0.9403969397937687
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -13,7 +40,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # ko_roberta_small_model
 
-This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on the klue dataset.
+This model is a fine-tuned version of [hyeonseo/ko_roberta_small_model](https://huggingface.co/hyeonseo/ko_roberta_small_model) on the klue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1864
+- Precision: 0.6827
+- Recall: 0.7254
+- F1: 0.7034
+- Accuracy: 0.9404
 
 ## Model description
 
@@ -40,6 +73,14 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: linear
 - num_epochs: 2
 
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2341        | 1.0   | 1313 | 0.2069          | 0.6516    | 0.6999 | 0.6749 | 0.9336   |
+| 0.16          | 2.0   | 2626 | 0.1864          | 0.6827    | 0.7254 | 0.7034 | 0.9404   |
+
+
 ### Framework versions
 
 - Transformers 4.28.0