End of training

README.md

@@ -14,20 +14,16 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.3110
-- Footer: {'precision': 0.9177158273381295, 'recall': 0.8951754385964912, 'f1': 0.9063055062166964, 'number': 2280}
-- Header: {'precision': 0.5789971617786187, 'recall': 0.6435331230283912, 'f1': 0.6095617529880478, 'number': 951}
-- Able: {'precision': 0.15821771611526148, 'recall': 0.4848732624693377, 'f1': 0.23858378595855967, 'number': 1223}
-- Aption: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 825}
-- Ext: {'precision': 0.25493653032440056, 'recall': 0.40928389470704785, 'f1': 0.3141770776751765, 'number': 3533}
-- Icture: {'precision': 0.013513513513513514, 'recall': 0.018092105263157895, 'f1': 0.01547116736990155, 'number': 608}
-- Itle: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}
-- Ootnote: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 145}
-- Ormula: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 360}
-- Overall Precision: 0.3480
-- Overall Recall: 0.4682
-- Overall F1: 0.3992
-- Overall Accuracy: 0.7076
+- Loss: 1.1562
+- Footer: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}
+- Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
+- Able: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}
+- Aption: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
+- Ext: {'precision': 0.06153846153846154, 'recall': 0.4, 'f1': 0.10666666666666667, 'number': 10}
+- Overall Precision: 0.0310
+- Overall Recall: 0.1739
+- Overall F1: 0.0526
+- Overall Accuracy: 0.8882
 
 ## Model description
 
@@ -56,10 +52,10 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Footer                                                                                                    | Header                                                                                                   | Able                                                                                                        | Aption                                                      | Ext                                                                                                          | Icture                                                                                                         | Itle                                                        | Ootnote                                                     | Ormula                                                      | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------:|:-----------------------------------------------------------:|:-----------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.451         | 1.0   | 500  | 1.4545          | {'precision': 0.7658186562296151, 'recall': 0.5149122807017544, 'f1': 0.6157880933648046, 'number': 2280} | {'precision': 1.0, 'recall': 0.0010515247108307045, 'f1': 0.0021008403361344537, 'number': 951}          | {'precision': 0.11016949152542373, 'recall': 0.3507767784137367, 'f1': 0.16767637287473128, 'number': 1223} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 825} | {'precision': 0.20891744548286603, 'recall': 0.30370789697141237, 'f1': 0.24754873687853268, 'number': 3533} | {'precision': 0.018442622950819672, 'recall': 0.029605263157894735, 'f1': 0.022727272727272728, 'number': 608} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 145} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 360} | 0.2335            | 0.2683         | 0.2497     | 0.6695           |
-| 0.2521        | 2.0   | 1000 | 1.3110          | {'precision': 0.9177158273381295, 'recall': 0.8951754385964912, 'f1': 0.9063055062166964, 'number': 2280} | {'precision': 0.5789971617786187, 'recall': 0.6435331230283912, 'f1': 0.6095617529880478, 'number': 951} | {'precision': 0.15821771611526148, 'recall': 0.4848732624693377, 'f1': 0.23858378595855967, 'number': 1223} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 825} | {'precision': 0.25493653032440056, 'recall': 0.40928389470704785, 'f1': 0.3141770776751765, 'number': 3533}  | {'precision': 0.013513513513513514, 'recall': 0.018092105263157895, 'f1': 0.01547116736990155, 'number': 608}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 145} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 360} | 0.3480            | 0.4682         | 0.3992     | 0.7076           |
+| Training Loss | Epoch | Step | Validation Loss | Footer                                                    | Header                                                    | Able                                                      | Aption                                                    | Ext                                                                                        | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 2.0796        | 1.0   | 5    | 1.4462          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.05063291139240506, 'recall': 0.4, 'f1': 0.0898876404494382, 'number': 10}  | 0.0255            | 0.1739         | 0.0444     | 0.8518           |
+| 1.2478        | 2.0   | 10   | 1.1562          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.06153846153846154, 'recall': 0.4, 'f1': 0.10666666666666667, 'number': 10} | 0.0310            | 0.1739         | 0.0526     | 0.8882           |
 
 
 ### Framework versions

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