update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.7383590141742317
+      value: 0.7071669427034283
     - name: Recall
       type: recall
-      value: 0.7303728891214774
+      value: 0.723286061789479
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -35,10 +35,10 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on the tweet_eval dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1203
-- Precision: 0.7384
-- Recall: 0.7304
-- Fscore: 0.7337
+- Loss: 1.2053
+- Precision: 0.7072
+- Recall: 0.7233
+- Fscore: 0.7124
 
 ## Model description
 
@@ -69,9 +69,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
-| 0.862         | 1.0   | 815  | 0.6941          | 0.7258    | 0.6530 | 0.6696 |
-| 0.5206        | 2.0   | 1630 | 0.8909          | 0.7391    | 0.6788 | 0.6994 |
-| 0.2662        | 3.0   | 2445 | 1.1203          | 0.7384    | 0.7304 | 0.7337 |
+| 0.8623        | 1.0   | 815  | 0.7198          | 0.7536    | 0.6312 | 0.6559 |
+| 0.5637        | 2.0   | 1630 | 0.8756          | 0.7213    | 0.7166 | 0.7160 |
+| 0.2845        | 3.0   | 2445 | 1.2053          | 0.7072    | 0.7233 | 0.7124 |
 
 
 ### Framework versions