update model card README.md

README.md

@@ -24,16 +24,16 @@ model-index:
     metrics:
     - name: Precision
       type: precision
-      value: 0.5752688172043011
+      value: 0.5565371024734982
     - name: Recall
       type: recall
-      value: 0.2974976830398517
+      value: 0.2919369786839666
     - name: F1
       type: f1
-      value: 0.39218081857055587
+      value: 0.3829787234042553
     - name: Accuracy
       type: accuracy
-      value: 0.9411312043093497
+      value: 0.9413449617374203
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -43,11 +43,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2787
-- Precision: 0.5753
-- Recall: 0.2975
-- F1: 0.3922
-- Accuracy: 0.9411
+- Loss: 0.2814
+- Precision: 0.5565
+- Recall: 0.2919
+- F1: 0.3830
+- Accuracy: 0.9413
 
 ## Model description
 
@@ -78,13 +78,13 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 213  | 0.2888          | 0.5409    | 0.2512 | 0.3430 | 0.9385   |
-| No log        | 2.0   | 426  | 0.2787          | 0.5753    | 0.2975 | 0.3922 | 0.9411   |
+| No log        | 1.0   | 213  | 0.2899          | 0.405     | 0.2252 | 0.2895 | 0.9368   |
+| No log        | 2.0   | 426  | 0.2814          | 0.5565    | 0.2919 | 0.3830 | 0.9413   |
 
 
 ### Framework versions
 
-- Transformers 4.29.1
+- Transformers 4.29.2
 - Pytorch 1.12.1
 - Datasets 2.11.0
 - Tokenizers 0.11.0