update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.6911154222440785
+      value: 0.7221058163048105
     - name: Recall
       type: recall
-      value: 0.7042874828316592
+      value: 0.7241535542602306
 ---
 
 <!-- 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: 1.2936
-- Precision: 0.6911
-- Recall: 0.7043
-- Fscore: 0.6964
+- Loss: 1.2559
+- Precision: 0.7221
+- Recall: 0.7242
+- Fscore: 0.7223
 
 ## Model description
 
@@ -69,9 +69,9 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
-| 0.8718        | 1.0   | 815  | 0.8270          | 0.7296    | 0.6338 | 0.6588 |
-| 0.5231        | 2.0   | 1630 | 1.0492          | 0.6918    | 0.6618 | 0.6724 |
-| 0.2617        | 3.0   | 2445 | 1.2936          | 0.6911    | 0.7043 | 0.6964 |
+| 0.8588        | 1.0   | 815  | 0.8342          | 0.7807    | 0.6117 | 0.6364 |
+| 0.5394        | 2.0   | 1630 | 0.9126          | 0.7363    | 0.6923 | 0.7096 |
+| 0.2805        | 3.0   | 2445 | 1.2559          | 0.7221    | 0.7242 | 0.7223 |
 
 
 ### Framework versions