update model card README.md

README.md

@@ -6,6 +6,8 @@ tags:
 metrics:
 - accuracy
 - f1
+- recall
+- precision
 model-index:
 - name: deberta-v3-xsmall-with-biblio-context-finetuned-review_classifier
   results: []
@@ -18,9 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.1580
-- Accuracy: 0.9505
-- F1: 0.7441
+- Loss: 0.0979
+- Accuracy: 0.9682
+- F1: 0.8332
+- Recall: 0.8466
+- Precision: 0.8202
 
 ## Model description
 
@@ -51,15 +55,15 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     |
-|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
-| 0.1551        | 1.0   | 6667  | 0.1765          | 0.9500   | 0.7184 |
-| 0.1249        | 2.0   | 13334 | 0.1580          | 0.9505   | 0.7441 |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Recall | Precision |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|:---------:|
+| 0.1539        | 1.0   | 6667  | 0.1237          | 0.9584   | 0.7668 | 0.7307 | 0.8067    |
+| 0.1271        | 2.0   | 13334 | 0.0979          | 0.9682   | 0.8332 | 0.8466 | 0.8202    |
 
 
 ### Framework versions
 
-- Transformers 4.18.0
-- Pytorch 1.11.0
-- Datasets 2.1.0
+- Transformers 4.20.1
+- Pytorch 1.12.0+cu102
+- Datasets 2.3.2
 - Tokenizers 0.12.1