update model card README.md

README.md

@@ -1,6 +1,4 @@
 ---
-language:
-- en
 tags:
 - generated_from_trainer
 datasets:
@@ -15,7 +13,7 @@ model-index:
       name: Text Classification
       type: text-classification
     dataset:
-      name: GLUE MRPC
+      name: glue
       type: glue
       config: mrpc
       split: validation
@@ -23,10 +21,10 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.6936274509803921
+      value: 0.7622549019607843
     - name: F1
       type: f1
-      value: 0.8085758039816232
+      value: 0.8380634390651085
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -34,12 +32,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 # hBERTv2_mrpc
 
-This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the GLUE MRPC dataset.
+This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2](https://huggingface.co/gokuls/bert_12_layer_model_v2) on the glue dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5772
-- Accuracy: 0.6936
-- F1: 0.8086
-- Combined Score: 0.7511
+- Loss: 0.9954
+- Accuracy: 0.7623
+- F1: 0.8381
+- Combined Score: 0.8002
 
 ## Model description
 
@@ -70,16 +68,16 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Accuracy | Combined Score | F1     | Validation Loss |
-|:-------------:|:-----:|:----:|:--------:|:--------------:|:------:|:---------------:|
-| 0.6388        | 1.0   | 15   | 0.6838   | 0.7480         | 0.8122 | 0.6297          |
-| 0.612         | 2.0   | 30   | 0.6887   | 0.7511         | 0.8135 | 0.6315          |
-| 0.5725        | 3.0   | 45   | 0.6936   | 0.7511         | 0.8086 | 0.5772          |
-| 0.512         | 4.0   | 60   | 0.6261   | 0.7010         | 0.8152 | 0.7581          |
-| 0.3924        | 5.0   | 75   | 0.6433   | 0.7279         | 0.8195 | 0.7737          |
-| 0.2592        | 6.0   | 90   | 0.7531   | 0.6863         | 0.7594 | 0.7228          |
-| 0.1689        | 7.0   | 105  | 0.7904   | 0.7377         | 0.8158 | 0.7768          |
-| 0.1292        | 8.0   | 120  | 0.9954   | 0.7623         | 0.8381 | 0.8002          |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 0.6388        | 1.0   | 15   | 0.6297          | 0.6838   | 0.8122 | 0.7480         |
+| 0.612         | 2.0   | 30   | 0.6315          | 0.6887   | 0.8135 | 0.7511         |
+| 0.5725        | 3.0   | 45   | 0.5772          | 0.6936   | 0.8086 | 0.7511         |
+| 0.512         | 4.0   | 60   | 0.6261          | 0.7010   | 0.8152 | 0.7581         |
+| 0.3924        | 5.0   | 75   | 0.6433          | 0.7279   | 0.8195 | 0.7737         |
+| 0.2592        | 6.0   | 90   | 0.7531          | 0.6863   | 0.7594 | 0.7228         |
+| 0.1689        | 7.0   | 105  | 0.7904          | 0.7377   | 0.8158 | 0.7768         |
+| 0.1292        | 8.0   | 120  | 0.9954          | 0.7623   | 0.8381 | 0.8002         |
 
 
 ### Framework versions