End of training

README.md

@@ -17,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6511
-- Answer: {'precision': 0.6761487964989059, 'recall': 0.7639060568603214, 'f1': 0.7173534532791643, 'number': 809}
-- Header: {'precision': 0.24545454545454545, 'recall': 0.226890756302521, 'f1': 0.23580786026200873, 'number': 119}
-- Question: {'precision': 0.7472245943637916, 'recall': 0.8215962441314554, 'f1': 0.7826475849731663, 'number': 1065}
-- Overall Precision: 0.6925
+- Loss: 0.6576
+- Answer: {'precision': 0.6760869565217391, 'recall': 0.7688504326328801, 'f1': 0.719491035280509, 'number': 809}
+- Header: {'precision': 0.29473684210526313, 'recall': 0.23529411764705882, 'f1': 0.2616822429906542, 'number': 119}
+- Question: {'precision': 0.7385398981324278, 'recall': 0.8169014084507042, 'f1': 0.7757467677218011, 'number': 1065}
+- Overall Precision: 0.6931
 - Overall Recall: 0.7627
-- Overall F1: 0.7259
-- Overall Accuracy: 0.7992
+- Overall F1: 0.7262
+- Overall Accuracy: 0.7966
 
 ## Model description
 
@@ -54,18 +54,18 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                     | Header                                                                                                         | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 1.7571        | 1.0   | 10   | 1.5405          | {'precision': 0.0392156862745098, 'recall': 0.0519159456118665, 'f1': 0.04468085106382978, 'number': 809}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                    | {'precision': 0.23129251700680273, 'recall': 0.3511737089201878, 'f1': 0.27889634601044, 'number': 1065}  | 0.1548            | 0.2087         | 0.1777     | 0.4539           |
-| 1.4002        | 2.0   | 20   | 1.2087          | {'precision': 0.21976592977893367, 'recall': 0.2088998763906057, 'f1': 0.21419518377693283, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                    | {'precision': 0.4806934594168637, 'recall': 0.5727699530516432, 'f1': 0.5227077977720652, 'number': 1065} | 0.3822            | 0.3909         | 0.3865     | 0.5991           |
-| 1.0781        | 3.0   | 30   | 0.9612          | {'precision': 0.437219730941704, 'recall': 0.4820766378244747, 'f1': 0.4585537918871252, 'number': 809}    | {'precision': 0.030303030303030304, 'recall': 0.008403361344537815, 'f1': 0.013157894736842105, 'number': 119} | {'precision': 0.6361233480176212, 'recall': 0.6779342723004694, 'f1': 0.6563636363636363, 'number': 1065} | 0.5403            | 0.5585         | 0.5492     | 0.6934           |
-| 0.8462        | 4.0   | 40   | 0.7985          | {'precision': 0.5972515856236786, 'recall': 0.6983930778739185, 'f1': 0.6438746438746439, 'number': 809}   | {'precision': 0.11363636363636363, 'recall': 0.04201680672268908, 'f1': 0.06134969325153375, 'number': 119}    | {'precision': 0.6884955752212389, 'recall': 0.7305164319248826, 'f1': 0.7088838268792711, 'number': 1065} | 0.6358            | 0.6764         | 0.6555     | 0.7564           |
-| 0.6873        | 5.0   | 50   | 0.7161          | {'precision': 0.6699779249448123, 'recall': 0.7503090234857849, 'f1': 0.707871720116618, 'number': 809}    | {'precision': 0.23529411764705882, 'recall': 0.16806722689075632, 'f1': 0.19607843137254902, 'number': 119}    | {'precision': 0.6994022203245089, 'recall': 0.7690140845070422, 'f1': 0.7325581395348838, 'number': 1065} | 0.6688            | 0.7255         | 0.6960     | 0.7858           |
-| 0.5786        | 6.0   | 60   | 0.6912          | {'precision': 0.6480505795574288, 'recall': 0.7601977750309024, 'f1': 0.6996587030716724, 'number': 809}   | {'precision': 0.2638888888888889, 'recall': 0.15966386554621848, 'f1': 0.19895287958115182, 'number': 119}     | {'precision': 0.7293700088731144, 'recall': 0.7718309859154929, 'f1': 0.7499999999999999, 'number': 1065} | 0.6778            | 0.7306         | 0.7032     | 0.7848           |
-| 0.5389        | 7.0   | 70   | 0.6760          | {'precision': 0.6835722160970231, 'recall': 0.7663782447466008, 'f1': 0.7226107226107226, 'number': 809}   | {'precision': 0.21978021978021978, 'recall': 0.16806722689075632, 'f1': 0.1904761904761905, 'number': 119}     | {'precision': 0.7195723684210527, 'recall': 0.8215962441314554, 'f1': 0.7672073651907059, 'number': 1065} | 0.6843            | 0.7602         | 0.7202     | 0.7929           |
-| 0.491         | 8.0   | 80   | 0.6643          | {'precision': 0.6782608695652174, 'recall': 0.7713226205191595, 'f1': 0.7218045112781956, 'number': 809}   | {'precision': 0.2708333333333333, 'recall': 0.2184873949579832, 'f1': 0.24186046511627907, 'number': 119}      | {'precision': 0.757847533632287, 'recall': 0.7934272300469484, 'f1': 0.7752293577981653, 'number': 1065}  | 0.7015            | 0.7501         | 0.7250     | 0.7969           |
-| 0.4543        | 9.0   | 90   | 0.6519          | {'precision': 0.6808743169398908, 'recall': 0.7700865265760197, 'f1': 0.722737819025522, 'number': 809}    | {'precision': 0.24509803921568626, 'recall': 0.21008403361344538, 'f1': 0.22624434389140272, 'number': 119}    | {'precision': 0.7564102564102564, 'recall': 0.8309859154929577, 'f1': 0.7919463087248323, 'number': 1065} | 0.7010            | 0.7692         | 0.7335     | 0.8003           |
-| 0.4461        | 10.0  | 100  | 0.6511          | {'precision': 0.6761487964989059, 'recall': 0.7639060568603214, 'f1': 0.7173534532791643, 'number': 809}   | {'precision': 0.24545454545454545, 'recall': 0.226890756302521, 'f1': 0.23580786026200873, 'number': 119}      | {'precision': 0.7472245943637916, 'recall': 0.8215962441314554, 'f1': 0.7826475849731663, 'number': 1065} | 0.6925            | 0.7627         | 0.7259     | 0.7992           |
+| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                         | Header                                                                                                        | Question                                                                                                  | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------:|:---------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.8473        | 1.0   | 10   | 1.5928          | {'precision': 0.018163471241170535, 'recall': 0.022249690976514216, 'f1': 0.020000000000000004, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                   | {'precision': 0.22706209453197404, 'recall': 0.2300469483568075, 'f1': 0.228544776119403, 'number': 1065} | 0.1271            | 0.1320         | 0.1295     | 0.3941           |
+| 1.4704        | 2.0   | 20   | 1.2787          | {'precision': 0.11602870813397129, 'recall': 0.11990111248454882, 'f1': 0.11793313069908813, 'number': 809}    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                   | {'precision': 0.4026946107784431, 'recall': 0.5051643192488263, 'f1': 0.4481466055810079, 'number': 1065} | 0.2924            | 0.3186         | 0.3049     | 0.5625           |
+| 1.1341        | 3.0   | 30   | 1.0026          | {'precision': 0.3333333333333333, 'recall': 0.33127317676143386, 'f1': 0.33230006199628026, 'number': 809}     | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                   | {'precision': 0.5989804587935429, 'recall': 0.6619718309859155, 'f1': 0.6289027653880465, 'number': 1065} | 0.4831            | 0.4882         | 0.4857     | 0.6604           |
+| 0.8967        | 4.0   | 40   | 0.8387          | {'precision': 0.571563981042654, 'recall': 0.7453646477132262, 'f1': 0.6469957081545066, 'number': 809}        | {'precision': 0.06976744186046512, 'recall': 0.025210084033613446, 'f1': 0.037037037037037035, 'number': 119} | {'precision': 0.6548748921484038, 'recall': 0.7126760563380282, 'f1': 0.6825539568345323, 'number': 1065} | 0.6048            | 0.6849         | 0.6424     | 0.7382           |
+| 0.723         | 5.0   | 50   | 0.7520          | {'precision': 0.5984174085064293, 'recall': 0.7478368355995055, 'f1': 0.6648351648351648, 'number': 809}       | {'precision': 0.1935483870967742, 'recall': 0.10084033613445378, 'f1': 0.13259668508287292, 'number': 119}    | {'precision': 0.6901041666666666, 'recall': 0.7464788732394366, 'f1': 0.7171853856562922, 'number': 1065} | 0.6346            | 0.7085         | 0.6695     | 0.7621           |
+| 0.6196        | 6.0   | 60   | 0.7171          | {'precision': 0.6231003039513677, 'recall': 0.7601977750309024, 'f1': 0.6848552338530067, 'number': 809}       | {'precision': 0.2125, 'recall': 0.14285714285714285, 'f1': 0.1708542713567839, 'number': 119}                 | {'precision': 0.7221238938053097, 'recall': 0.7661971830985915, 'f1': 0.743507972665148, 'number': 1065}  | 0.6591            | 0.7265         | 0.6912     | 0.7734           |
+| 0.5747        | 7.0   | 70   | 0.6993          | {'precision': 0.6506410256410257, 'recall': 0.7527812113720643, 'f1': 0.6979942693409743, 'number': 809}       | {'precision': 0.2558139534883721, 'recall': 0.18487394957983194, 'f1': 0.21463414634146344, 'number': 119}    | {'precision': 0.6894060995184591, 'recall': 0.8065727699530516, 'f1': 0.7434011250540891, 'number': 1065} | 0.6570            | 0.7476         | 0.6994     | 0.7841           |
+| 0.5292        | 8.0   | 80   | 0.6785          | {'precision': 0.6484536082474227, 'recall': 0.7775030902348579, 'f1': 0.7071388420460932, 'number': 809}       | {'precision': 0.29069767441860467, 'recall': 0.21008403361344538, 'f1': 0.24390243902439027, 'number': 119}   | {'precision': 0.7459893048128342, 'recall': 0.7859154929577464, 'f1': 0.7654320987654322, 'number': 1065} | 0.6846            | 0.7481         | 0.7149     | 0.7893           |
+| 0.4862        | 9.0   | 90   | 0.6637          | {'precision': 0.658008658008658, 'recall': 0.7515451174289246, 'f1': 0.7016733987305251, 'number': 809}        | {'precision': 0.28125, 'recall': 0.226890756302521, 'f1': 0.2511627906976744, 'number': 119}                  | {'precision': 0.7287853577371048, 'recall': 0.8225352112676056, 'f1': 0.7728275253639171, 'number': 1065} | 0.6800            | 0.7582         | 0.7170     | 0.7931           |
+| 0.4795        | 10.0  | 100  | 0.6576          | {'precision': 0.6760869565217391, 'recall': 0.7688504326328801, 'f1': 0.719491035280509, 'number': 809}        | {'precision': 0.29473684210526313, 'recall': 0.23529411764705882, 'f1': 0.2616822429906542, 'number': 119}    | {'precision': 0.7385398981324278, 'recall': 0.8169014084507042, 'f1': 0.7757467677218011, 'number': 1065} | 0.6931            | 0.7627         | 0.7262     | 0.7966           |
 
 
 ### Framework versions

logs/events.out.tfevents.1719801435.HCIDC-SV-DMZ-ORC-NODE02.1951490.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 12085
+oid sha256:b8f16a93c977a1a43284cfa2891f887c23e3dcddb349a7cf2a499011ddad7d5d
+size 12433