Model save

README.md

@@ -16,12 +16,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0662
-- Np: {'precision': 0.9635027246229882, 'recall': 0.9720020455126566, 'f1': 0.9677337236683001, 'number': 7822}
-- Overall Precision: 0.9635
-- Overall Recall: 0.9720
-- Overall F1: 0.9677
-- Overall Accuracy: 0.9817
+- Loss: 0.0673
+- Np: {'precision': 0.9644760213143873, 'recall': 0.9718742009716185, 'f1': 0.968160978094753, 'number': 7822}
+- Overall Precision: 0.9645
+- Overall Recall: 0.9719
+- Overall F1: 0.9682
+- Overall Accuracy: 0.9813
 
 ## Model description
 
@@ -50,9 +50,9 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Np                                                                                                        | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.064         | 1.0   | 3751 | 0.0662          | {'precision': 0.9635027246229882, 'recall': 0.9720020455126566, 'f1': 0.9677337236683001, 'number': 7822} | 0.9635            | 0.9720         | 0.9677     | 0.9817           |
+| Training Loss | Epoch | Step | Validation Loss | Np                                                                                                       | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.0646        | 1.0   | 3751 | 0.0673          | {'precision': 0.9644760213143873, 'recall': 0.9718742009716185, 'f1': 0.968160978094753, 'number': 7822} | 0.9645            | 0.9719         | 0.9682     | 0.9813           |
 
 
 ### Framework versions