End of training

README.md

@@ -13,19 +13,18 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model was trained from scratch on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 2.5944
-- Comment: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4}
-- Date: {'precision': 0.875, 'recall': 0.2413793103448276, 'f1': 0.3783783783783784, 'number': 145}
-- Labname: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
-- Laboratory: {'precision': 0.6, 'recall': 0.13636363636363635, 'f1': 0.22222222222222218, 'number': 22}
-- Measure: {'precision': 0.4857142857142857, 'recall': 0.4594594594594595, 'f1': 0.47222222222222227, 'number': 37}
-- Name: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
-- Ref Value: {'precision': 0.3398876404494382, 'recall': 0.8832116788321168, 'f1': 0.4908722109533469, 'number': 137}
-- Result: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5}
-- Overall Precision: 0.4027
-- Overall Recall: 0.4986
-- Overall F1: 0.4456
-- Overall Accuracy: 0.4200
+- Loss: 0.4919
+- Comment: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6}
+- Date: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3}
+- Labname: {'precision': 0.5833333333333334, 'recall': 0.6666666666666666, 'f1': 0.6222222222222222, 'number': 21}
+- Laboratory: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1}
+- Measure: {'precision': 0.5833333333333334, 'recall': 0.7777777777777778, 'f1': 0.6666666666666666, 'number': 9}
+- Ref Value: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8}
+- Result: {'precision': 0.25, 'recall': 0.25, 'f1': 0.25, 'number': 12}
+- Overall Precision: 0.4528
+- Overall Recall: 0.4
+- Overall F1: 0.4248
+- Overall Accuracy: 0.8698
 
 ## Model description
 
@@ -55,13 +54,13 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Comment                                                   | Date                                                                                                      | Labname                                                   | Laboratory                                                                                 | Measure                                                                                                  | Name                                                      | Ref Value                                                                                                  | Result                                                    | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 2.51          | 5.0   | 5    | 2.6583          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 145}                                               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 37}                                               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.2601279317697228, 'recall': 0.8905109489051095, 'f1': 0.40264026402640263, 'number': 137}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | 0.2601            | 0.3456         | 0.2968     | 0.2601           |
-| 1.3802        | 10.0  | 10   | 2.5067          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 145}                                               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 37}                                               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.2601279317697228, 'recall': 0.8905109489051095, 'f1': 0.40264026402640263, 'number': 137}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | 0.2601            | 0.3456         | 0.2968     | 0.2601           |
-| 0.9957        | 15.0  | 15   | 2.4104          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4} | {'precision': 0.5396825396825397, 'recall': 0.23448275862068965, 'f1': 0.3269230769230769, 'number': 145} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 37}                                               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.30049261083743845, 'recall': 0.8905109489051095, 'f1': 0.44935543278084716, 'number': 137} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | 0.3326            | 0.4419         | 0.3796     | 0.3326           |
-| 0.6893        | 20.0  | 20   | 2.5476          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4} | {'precision': 0.5352112676056338, 'recall': 0.2620689655172414, 'f1': 0.3518518518518518, 'number': 145}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 22}                                 | {'precision': 0.5, 'recall': 0.3783783783783784, 'f1': 0.4307692307692308, 'number': 37}                 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.33152173913043476, 'recall': 0.8905109489051095, 'f1': 0.48316831683168315, 'number': 137} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | 0.3726            | 0.4929         | 0.4244     | 0.3817           |
-| 0.527         | 25.0  | 25   | 2.5944          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 4} | {'precision': 0.875, 'recall': 0.2413793103448276, 'f1': 0.3783783783783784, 'number': 145}               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.6, 'recall': 0.13636363636363635, 'f1': 0.22222222222222218, 'number': 22} | {'precision': 0.4857142857142857, 'recall': 0.4594594594594595, 'f1': 0.47222222222222227, 'number': 37} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.3398876404494382, 'recall': 0.8832116788321168, 'f1': 0.4908722109533469, 'number': 137}   | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | 0.4027            | 0.4986         | 0.4456     | 0.4200           |
+| Training Loss | Epoch | Step | Validation Loss | Comment                                                   | Date                                                      | Labname                                                                                                 | Laboratory                                                | Measure                                                                                                | Ref Value                                                 | Result                                                                                     | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 2.4398        | 5.0   | 5    | 1.5928          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21}                                              | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}                                              | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 12}                                 | 0.0               | 0.0            | 0.0        | 0.5850           |
+| 1.4788        | 10.0  | 10   | 1.1857          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 21}                                              | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}                                              | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 12}                                 | 0.0               | 0.0            | 0.0        | 0.6512           |
+| 0.9806        | 15.0  | 15   | 0.8188          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.21875, 'recall': 0.3333333333333333, 'f1': 0.2641509433962264, 'number': 21}            | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.5, 'recall': 0.1111111111111111, 'f1': 0.1818181818181818, 'number': 9}                | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 12}                                 | 0.1667            | 0.1333         | 0.1481     | 0.7660           |
+| 0.6358        | 20.0  | 20   | 0.5763          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.41935483870967744, 'recall': 0.6190476190476191, 'f1': 0.5, 'number': 21}               | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.7, 'recall': 0.7777777777777778, 'f1': 0.7368421052631577, 'number': 9}                | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.42857142857142855, 'recall': 0.25, 'f1': 0.3157894736842105, 'number': 12} | 0.4182            | 0.3833         | 0.4        | 0.8675           |
+| 0.4712        | 25.0  | 25   | 0.4919          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 6} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 3} | {'precision': 0.5833333333333334, 'recall': 0.6666666666666666, 'f1': 0.6222222222222222, 'number': 21} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.5833333333333334, 'recall': 0.7777777777777778, 'f1': 0.6666666666666666, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 8} | {'precision': 0.25, 'recall': 0.25, 'f1': 0.25, 'number': 12}                              | 0.4528            | 0.4            | 0.4248     | 0.8698           |
 
 
 ### Framework versions

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