Model save

README.md

@@ -43,14 +43,14 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Date                                                       | Loc                                                                                                      | Org                                                                                                     | Per                                                        | Price                                                                                   | Product                                                    | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:---------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| No log        | 1.0   | 100  | 0.1526          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 36} | {'precision': 0.8809523809523809, 'recall': 0.9098360655737705, 'f1': 0.8951612903225806, 'number': 122} | {'precision': 0.5068493150684932, 'recall': 0.6065573770491803, 'f1': 0.5522388059701493, 'number': 61} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 62} | {'precision': 0.839622641509434, 'recall': 1.0, 'f1': 0.9128205128205129, 'number': 89} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 16} | 0.8313            | 0.8679         | 0.8492     | 0.9685           |
+| Training Loss | Epoch | Step | Validation Loss | Date                                                       | Loc                                                                                             | Org                                                                                                     | Per                                                        | Price                                                      | Product                                                                                                 | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------:|:-----------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------:|:----------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| No log        | 1.0   | 100  | 0.0445          | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 39} | {'precision': 0.8984375, 'recall': 0.9274193548387096, 'f1': 0.9126984126984127, 'number': 124} | {'precision': 0.8448275862068966, 'recall': 0.8305084745762712, 'f1': 0.8376068376068375, 'number': 59} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 70} | {'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 79} | {'precision': 0.9230769230769231, 'recall': 0.9230769230769231, 'f1': 0.9230769230769231, 'number': 13} | 0.9406            | 0.9479         | 0.9442     | 0.9859           |
 
 
 ### Framework versions
 
-- Transformers 4.47.0
+- Transformers 4.47.1
 - Pytorch 2.5.1+cu121
 - Datasets 3.2.0
 - Tokenizers 0.21.0