update model card README.md

README.md

@@ -21,7 +21,7 @@ model-index:
     metrics:
     - name: Accuracy
       type: accuracy
-      value: 0.939
+      value: 0.9385
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -29,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 # jq_emo_distilbert
 
-This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the emotion dataset.
+This model is a fine-tuned version of [tingtone/jq_emo_distilbert](https://huggingface.co/tingtone/jq_emo_distilbert) on the emotion dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2100
-- Accuracy: 0.939
+- Loss: 0.3185
+- Accuracy: 0.9385
 
 ## Model description
 
@@ -64,16 +64,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|
-| 1.6731        | 1.0   | 1000  | 1.5737          | 0.4805   |
-| 1.224         | 2.0   | 2000  | 1.1049          | 0.5915   |
-| 0.8266        | 3.0   | 3000  | 0.7033          | 0.761    |
-| 0.4635        | 4.0   | 4000  | 0.3884          | 0.8845   |
-| 0.2832        | 5.0   | 5000  | 0.2466          | 0.9145   |
-| 0.1855        | 6.0   | 6000  | 0.2112          | 0.926    |
-| 0.1552        | 7.0   | 7000  | 0.1978          | 0.9285   |
-| 0.1426        | 8.0   | 8000  | 0.1937          | 0.9345   |
-| 0.1308        | 9.0   | 9000  | 0.2093          | 0.932    |
-| 0.1127        | 10.0  | 10000 | 0.2100          | 0.939    |
+| 0.1042        | 1.0   | 1000  | 0.1816          | 0.932    |
+| 0.0998        | 2.0   | 2000  | 0.1799          | 0.934    |
+| 0.0957        | 3.0   | 3000  | 0.2015          | 0.935    |
+| 0.0846        | 4.0   | 4000  | 0.2129          | 0.9335   |
+| 0.0943        | 5.0   | 5000  | 0.2215          | 0.935    |
+| 0.075         | 6.0   | 6000  | 0.2627          | 0.9375   |
+| 0.0607        | 7.0   | 7000  | 0.2908          | 0.9345   |
+| 0.0636        | 8.0   | 8000  | 0.3207          | 0.935    |
+| 0.0953        | 9.0   | 9000  | 0.3165          | 0.936    |
+| 0.0748        | 10.0  | 10000 | 0.3185          | 0.9385   |
 
 
 ### Framework versions