update model card README.md

README.md

@@ -22,10 +22,10 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.7505623807659564
+      value: 0.6979544225842089
     - name: Recall
       type: recall
-      value: 0.7243031825553111
+      value: 0.7110390879680959
 ---
 
 <!-- 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: 1.1413
-- Precision: 0.7506
-- Recall: 0.7243
-- Fscore: 0.7340
+- Loss: 1.2737
+- Precision: 0.6980
+- Recall: 0.7110
+- Fscore: 0.7026
 
 ## Model description
 
@@ -69,14 +69,14 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
-| 0.8556        | 1.0   | 815  | 0.7854          | 0.7461    | 0.5929 | 0.6088 |
-| 0.5369        | 2.0   | 1630 | 0.9014          | 0.7549    | 0.7278 | 0.7359 |
-| 0.2571        | 3.0   | 2445 | 1.1413          | 0.7506    | 0.7243 | 0.7340 |
+| 0.877         | 1.0   | 815  | 0.8045          | 0.7449    | 0.6495 | 0.6765 |
+| 0.5462        | 2.0   | 1630 | 1.0057          | 0.7148    | 0.6566 | 0.6774 |
+| 0.2691        | 3.0   | 2445 | 1.2737          | 0.6980    | 0.7110 | 0.7026 |
 
 
 ### Framework versions
 
-- Transformers 4.28.0
+- Transformers 4.29.2
 - Pytorch 2.0.1+cu118
 - Datasets 2.12.0
 - Tokenizers 0.13.3