Update README.md

README.md

@@ -5,29 +5,33 @@ tags:
 - generated_from_trainer
 metrics:
 - accuracy
+- f1
+- recall
+- precision
 model-index:
 - name: bert-large-uncased-Fake_Reviews_Classifier
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-
 # bert-large-uncased-Fake_Reviews_Classifier
 
-This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on the None dataset.
+This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased).
+
 It achieves the following results on the evaluation set:
 - Loss: 0.5336
 - Accuracy: 0.8381
-- Weighted f1: 0.8142
-- Micro f1: 0.8381
-- Macro f1: 0.6308
-- Weighted recall: 0.8381
-- Micro recall: 0.8381
-- Macro recall: 0.6090
-- Weighted precision: 0.8101
-- Micro precision: 0.8381
-- Macro precision: 0.7029
+- F1
+  - Weighted: 0.8142
+  - Micro: 0.8381
+  - Macro: 0.6308
+- Recall
+  - Weighted: 0.8381
+  - Micro: 0.8381
+  - Macro: 0.6090
+- Precision
+  - Weighted: 0.8101
+  - Micro: 0.8381
+  - Macro: 0.7029
 
 ## Model description
 
@@ -56,7 +60,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Weighted F1 | Micro F1 | Macro F1 | Weighted Recall | Micro Recall | Macro Recall | Weighted Precision | Micro Precision | Macro Precision |
 |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:|
 | 0.633         | 1.0   | 10438 | 0.5608          | 0.8261   | 0.7914      | 0.8261   | 0.5745   | 0.8261          | 0.8261       | 0.5643       | 0.7844             | 0.8261          | 0.6542          |
 | 0.6029        | 2.0   | 20876 | 0.6490          | 0.8331   | 0.7724      | 0.8331   | 0.5060   | 0.8331          | 0.8331       | 0.5239       | 0.7892             | 0.8331          | 0.6929          |
@@ -70,4 +74,4 @@ The following hyperparameters were used during training:
 - Transformers 4.31.0
 - Pytorch 2.0.1
 - Datasets 2.13.1
-- Tokenizers 0.13.3
+- Tokenizers 0.13.3