End of training

README.md

@@ -4,6 +4,11 @@ license: apache-2.0
 base_model: bert-base-uncased
 tags:
 - generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
 model-index:
 - name: phishing_detection_fine_tuned_bert
   results: []
@@ -16,7 +21,11 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4029
+- Loss: 0.2946
+- Accuracy: 0.8809
+- F1: 0.8809
+- Precision: 0.8808
+- Recall: 0.8809
 
 ## Model description
 
@@ -42,17 +51,13 @@ The following hyperparameters were used during training:
 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- num_epochs: 5
+- num_epochs: 1
 
 ### Training results
 
-| Training Loss | Epoch | Step  | Validation Loss |
-|:-------------:|:-----:|:-----:|:---------------:|
-| 0.5508        | 1.0   | 3710  | 0.5307          |
-| 0.5149        | 2.0   | 7420  | 0.4215          |
-| 0.595         | 3.0   | 11130 | 0.5736          |
-| 0.5279        | 4.0   | 14840 | 0.4757          |
-| 0.427         | 5.0   | 18550 | 0.4029          |
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.2703        | 1.0   | 3622 | 0.2946          | 0.8809   | 0.8809 | 0.8808    | 0.8809 |
 
 
 ### Framework versions