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: 0.7113
-- Answer: {'precision': 0.7158962795941376, 'recall': 0.7849196538936959, 'f1': 0.7488207547169812, 'number': 809}
-- Header: {'precision': 0.3418803418803419, 'recall': 0.33613445378151263, 'f1': 0.3389830508474576, 'number': 119}
-- Question: {'precision': 0.7726480836236934, 'recall': 0.8328638497652582, 'f1': 0.8016267510167194, 'number': 1065}
-- Overall Precision: 0.7258
-- Overall Recall: 0.7837
-- Overall F1: 0.7537
-- Overall Accuracy: 0.8028
+- Loss: 0.6782
+- Answer: {'precision': 0.694206008583691, 'recall': 0.799752781211372, 'f1': 0.7432510051694429, 'number': 809}
+- Header: {'precision': 0.30952380952380953, 'recall': 0.3277310924369748, 'f1': 0.31836734693877555, 'number': 119}
+- Question: {'precision': 0.769098712446352, 'recall': 0.8413145539906103, 'f1': 0.8035874439461884, 'number': 1065}
+- Overall Precision: 0.7117
+- Overall Recall: 0.7938
+- Overall F1: 0.7505
+- Overall Accuracy: 0.8017
 
 ## Model description
 
@@ -54,23 +54,23 @@ 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 |
-|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 1.7452        | 1.0   | 10   | 1.5534          | {'precision': 0.03913894324853229, 'recall': 0.049443757725587144, 'f1': 0.043691971600218454, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.26121794871794873, 'recall': 0.3061032863849765, 'f1': 0.2818849978383052, 'number': 1065} | 0.1612            | 0.1836         | 0.1717     | 0.4436           |
-| 1.3859        | 2.0   | 20   | 1.1959          | {'precision': 0.3140161725067385, 'recall': 0.2880098887515451, 'f1': 0.30045132172791744, 'number': 809}     | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.5303030303030303, 'recall': 0.5915492957746479, 'f1': 0.559254327563249, 'number': 1065}   | 0.4467            | 0.4330         | 0.4397     | 0.6150           |
-| 1.037         | 3.0   | 30   | 0.8960          | {'precision': 0.5337078651685393, 'recall': 0.5871446229913473, 'f1': 0.559152442613302, 'number': 809}       | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.616597510373444, 'recall': 0.6976525821596244, 'f1': 0.654625550660793, 'number': 1065}    | 0.5724            | 0.6111         | 0.5911     | 0.7266           |
-| 0.7743        | 4.0   | 40   | 0.7486          | {'precision': 0.6307363927427961, 'recall': 0.73053152039555, 'f1': 0.6769759450171822, 'number': 809}        | {'precision': 0.1044776119402985, 'recall': 0.058823529411764705, 'f1': 0.07526881720430108, 'number': 119} | {'precision': 0.6512013256006628, 'recall': 0.7380281690140845, 'f1': 0.6919014084507042, 'number': 1065}  | 0.6260            | 0.6944         | 0.6584     | 0.7694           |
-| 0.6151        | 5.0   | 50   | 0.7067          | {'precision': 0.6449511400651465, 'recall': 0.7342398022249691, 'f1': 0.6867052023121387, 'number': 809}      | {'precision': 0.21686746987951808, 'recall': 0.15126050420168066, 'f1': 0.1782178217821782, 'number': 119}  | {'precision': 0.6762589928057554, 'recall': 0.7943661971830986, 'f1': 0.7305699481865285, 'number': 1065}  | 0.6466            | 0.7316         | 0.6864     | 0.7804           |
-| 0.5319        | 6.0   | 60   | 0.6947          | {'precision': 0.6685022026431718, 'recall': 0.7503090234857849, 'f1': 0.707047175305766, 'number': 809}       | {'precision': 0.24096385542168675, 'recall': 0.16806722689075632, 'f1': 0.19801980198019803, 'number': 119} | {'precision': 0.7186700767263428, 'recall': 0.7915492957746478, 'f1': 0.7533512064343162, 'number': 1065}  | 0.6793            | 0.7376         | 0.7072     | 0.7920           |
-| 0.4602        | 7.0   | 70   | 0.6794          | {'precision': 0.6762430939226519, 'recall': 0.7564894932014833, 'f1': 0.7141190198366394, 'number': 809}      | {'precision': 0.28225806451612906, 'recall': 0.29411764705882354, 'f1': 0.2880658436213992, 'number': 119}  | {'precision': 0.7359307359307359, 'recall': 0.7981220657276995, 'f1': 0.7657657657657657, 'number': 1065}  | 0.6854            | 0.7511         | 0.7168     | 0.7980           |
-| 0.4119        | 8.0   | 80   | 0.6743          | {'precision': 0.6659619450317125, 'recall': 0.7787391841779975, 'f1': 0.7179487179487181, 'number': 809}      | {'precision': 0.32, 'recall': 0.2689075630252101, 'f1': 0.2922374429223744, 'number': 119}                  | {'precision': 0.7383820998278829, 'recall': 0.8056338028169014, 'f1': 0.7705433318365513, 'number': 1065}  | 0.6884            | 0.7627         | 0.7236     | 0.7996           |
-| 0.3663        | 9.0   | 90   | 0.6797          | {'precision': 0.6924803591470258, 'recall': 0.7626699629171817, 'f1': 0.7258823529411764, 'number': 809}      | {'precision': 0.3017241379310345, 'recall': 0.29411764705882354, 'f1': 0.29787234042553185, 'number': 119}  | {'precision': 0.7450812660393499, 'recall': 0.8178403755868544, 'f1': 0.7797672336615935, 'number': 1065}  | 0.6999            | 0.7642         | 0.7306     | 0.7968           |
-| 0.3556        | 10.0  | 100  | 0.6809          | {'precision': 0.699666295884316, 'recall': 0.7775030902348579, 'f1': 0.7365339578454333, 'number': 809}       | {'precision': 0.34615384615384615, 'recall': 0.3025210084033613, 'f1': 0.32286995515695066, 'number': 119}  | {'precision': 0.7615720524017467, 'recall': 0.8187793427230047, 'f1': 0.7891402714932126, 'number': 1065}  | 0.7155            | 0.7712         | 0.7423     | 0.8013           |
-| 0.3051        | 11.0  | 110  | 0.6935          | {'precision': 0.6933187294633077, 'recall': 0.7824474660074165, 'f1': 0.7351916376306621, 'number': 809}      | {'precision': 0.3217391304347826, 'recall': 0.31092436974789917, 'f1': 0.3162393162393162, 'number': 119}   | {'precision': 0.764102564102564, 'recall': 0.8394366197183099, 'f1': 0.7999999999999999, 'number': 1065}   | 0.7116            | 0.7847         | 0.7464     | 0.8018           |
-| 0.2905        | 12.0  | 120  | 0.7059          | {'precision': 0.7200929152148664, 'recall': 0.7663782447466008, 'f1': 0.7425149700598803, 'number': 809}      | {'precision': 0.35185185185185186, 'recall': 0.31932773109243695, 'f1': 0.33480176211453744, 'number': 119} | {'precision': 0.7692307692307693, 'recall': 0.8262910798122066, 'f1': 0.7967406066093254, 'number': 1065}  | 0.7279            | 0.7717         | 0.7491     | 0.7986           |
-| 0.2804        | 13.0  | 130  | 0.7065          | {'precision': 0.709211986681465, 'recall': 0.7898640296662547, 'f1': 0.7473684210526316, 'number': 809}       | {'precision': 0.35135135135135137, 'recall': 0.3277310924369748, 'f1': 0.3391304347826087, 'number': 119}   | {'precision': 0.7648068669527897, 'recall': 0.8366197183098592, 'f1': 0.7991031390134529, 'number': 1065}  | 0.7207            | 0.7873         | 0.7525     | 0.8008           |
-| 0.261         | 14.0  | 140  | 0.7096          | {'precision': 0.713963963963964, 'recall': 0.7836835599505563, 'f1': 0.7472009428403065, 'number': 809}       | {'precision': 0.3448275862068966, 'recall': 0.33613445378151263, 'f1': 0.3404255319148936, 'number': 119}   | {'precision': 0.7722943722943723, 'recall': 0.8375586854460094, 'f1': 0.8036036036036036, 'number': 1065}  | 0.7253            | 0.7858         | 0.7543     | 0.8028           |
-| 0.2537        | 15.0  | 150  | 0.7113          | {'precision': 0.7158962795941376, 'recall': 0.7849196538936959, 'f1': 0.7488207547169812, 'number': 809}      | {'precision': 0.3418803418803419, 'recall': 0.33613445378151263, 'f1': 0.3389830508474576, 'number': 119}   | {'precision': 0.7726480836236934, 'recall': 0.8328638497652582, 'f1': 0.8016267510167194, 'number': 1065}  | 0.7258            | 0.7837         | 0.7537     | 0.8028           |
+| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                        | Header                                                                                                      | Question                                                                                                     | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.8074        | 1.0   | 10   | 1.5777          | {'precision': 0.03731343283582089, 'recall': 0.037082818294190356, 'f1': 0.037197768133911964, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.25181598062953997, 'recall': 0.19530516431924883, 'f1': 0.21998942358540455, 'number': 1065} | 0.1460            | 0.1194         | 0.1314     | 0.3680           |
+| 1.4231        | 2.0   | 20   | 1.2292          | {'precision': 0.24720068906115417, 'recall': 0.3547589616810878, 'f1': 0.29137055837563447, 'number': 809}    | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.4146341463414634, 'recall': 0.5906103286384976, 'f1': 0.4872192099147947, 'number': 1065}    | 0.3420            | 0.4596         | 0.3922     | 0.6004           |
+| 1.0745        | 3.0   | 30   | 0.9226          | {'precision': 0.4796828543111992, 'recall': 0.5982694684796045, 'f1': 0.5324532453245325, 'number': 809}      | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                 | {'precision': 0.5457122608079377, 'recall': 0.7230046948356808, 'f1': 0.6219709208400647, 'number': 1065}    | 0.5102            | 0.6292         | 0.5635     | 0.7057           |
+| 0.8254        | 4.0   | 40   | 0.7937          | {'precision': 0.569215876089061, 'recall': 0.7268232385661311, 'f1': 0.6384364820846906, 'number': 809}       | {'precision': 0.1864406779661017, 'recall': 0.09243697478991597, 'f1': 0.12359550561797754, 'number': 119}  | {'precision': 0.6400651465798045, 'recall': 0.7380281690140845, 'f1': 0.6855647623201047, 'number': 1065}    | 0.5970            | 0.6949         | 0.6422     | 0.7517           |
+| 0.6703        | 5.0   | 50   | 0.7225          | {'precision': 0.6260162601626016, 'recall': 0.761433868974042, 'f1': 0.6871165644171779, 'number': 809}       | {'precision': 0.2413793103448276, 'recall': 0.17647058823529413, 'f1': 0.2038834951456311, 'number': 119}   | {'precision': 0.6737421383647799, 'recall': 0.8046948356807512, 'f1': 0.7334189131364998, 'number': 1065}    | 0.6376            | 0.7496         | 0.6891     | 0.7784           |
+| 0.5723        | 6.0   | 60   | 0.6881          | {'precision': 0.6349206349206349, 'recall': 0.7911001236093943, 'f1': 0.7044578976334617, 'number': 809}      | {'precision': 0.2127659574468085, 'recall': 0.16806722689075632, 'f1': 0.18779342723004694, 'number': 119}  | {'precision': 0.7215081405312768, 'recall': 0.7906103286384977, 'f1': 0.7544802867383513, 'number': 1065}    | 0.6620            | 0.7536         | 0.7048     | 0.7851           |
+| 0.4989        | 7.0   | 70   | 0.6636          | {'precision': 0.6565040650406504, 'recall': 0.7985166872682324, 'f1': 0.720580033463469, 'number': 809}       | {'precision': 0.27, 'recall': 0.226890756302521, 'f1': 0.24657534246575347, 'number': 119}                  | {'precision': 0.7410636442894507, 'recall': 0.7981220657276995, 'f1': 0.7685352622061482, 'number': 1065}    | 0.6827            | 0.7642         | 0.7211     | 0.7938           |
+| 0.4428        | 8.0   | 80   | 0.6578          | {'precision': 0.6629441624365482, 'recall': 0.8071693448702101, 'f1': 0.7279821627647713, 'number': 809}      | {'precision': 0.2803738317757009, 'recall': 0.25210084033613445, 'f1': 0.2654867256637167, 'number': 119}   | {'precision': 0.7472340425531915, 'recall': 0.8244131455399061, 'f1': 0.7839285714285714, 'number': 1065}    | 0.6886            | 0.7832         | 0.7329     | 0.7947           |
+| 0.3904        | 9.0   | 90   | 0.6481          | {'precision': 0.6839872746553552, 'recall': 0.7972805933250927, 'f1': 0.7363013698630138, 'number': 809}      | {'precision': 0.27927927927927926, 'recall': 0.2605042016806723, 'f1': 0.26956521739130435, 'number': 119}  | {'precision': 0.7502081598667777, 'recall': 0.8460093896713615, 'f1': 0.795233892321271, 'number': 1065}     | 0.6993            | 0.7913         | 0.7425     | 0.8017           |
+| 0.3817        | 10.0  | 100  | 0.6495          | {'precision': 0.6941176470588235, 'recall': 0.8022249690976514, 'f1': 0.7442660550458714, 'number': 809}      | {'precision': 0.27049180327868855, 'recall': 0.2773109243697479, 'f1': 0.27385892116182575, 'number': 119}  | {'precision': 0.7609630266552021, 'recall': 0.8309859154929577, 'f1': 0.7944344703770198, 'number': 1065}    | 0.7059            | 0.7863         | 0.7439     | 0.8048           |
+| 0.3252        | 11.0  | 110  | 0.6711          | {'precision': 0.697452229299363, 'recall': 0.8121137206427689, 'f1': 0.750428326670474, 'number': 809}        | {'precision': 0.29411764705882354, 'recall': 0.29411764705882354, 'f1': 0.29411764705882354, 'number': 119} | {'precision': 0.76592082616179, 'recall': 0.8356807511737089, 'f1': 0.7992815446789402, 'number': 1065}      | 0.7117            | 0.7938         | 0.7505     | 0.7979           |
+| 0.3099        | 12.0  | 120  | 0.6680          | {'precision': 0.6943556975505857, 'recall': 0.8059332509270705, 'f1': 0.745995423340961, 'number': 809}       | {'precision': 0.2966101694915254, 'recall': 0.29411764705882354, 'f1': 0.2953586497890296, 'number': 119}   | {'precision': 0.7663793103448275, 'recall': 0.8347417840375587, 'f1': 0.7991011235955056, 'number': 1065}    | 0.7109            | 0.7908         | 0.7487     | 0.8008           |
+| 0.2926        | 13.0  | 130  | 0.6750          | {'precision': 0.689727463312369, 'recall': 0.8133498145859085, 'f1': 0.7464549064095293, 'number': 809}       | {'precision': 0.32142857142857145, 'recall': 0.3025210084033613, 'f1': 0.3116883116883117, 'number': 119}   | {'precision': 0.7805944055944056, 'recall': 0.8384976525821596, 'f1': 0.8085106382978724, 'number': 1065}    | 0.7181            | 0.7963         | 0.7552     | 0.8020           |
+| 0.2769        | 14.0  | 140  | 0.6757          | {'precision': 0.6956989247311828, 'recall': 0.799752781211372, 'f1': 0.7441058079355952, 'number': 809}       | {'precision': 0.312, 'recall': 0.3277310924369748, 'f1': 0.31967213114754095, 'number': 119}                | {'precision': 0.7677029360967185, 'recall': 0.8347417840375587, 'f1': 0.7998200629779576, 'number': 1065}    | 0.7117            | 0.7903         | 0.7489     | 0.8024           |
+| 0.2743        | 15.0  | 150  | 0.6782          | {'precision': 0.694206008583691, 'recall': 0.799752781211372, 'f1': 0.7432510051694429, 'number': 809}        | {'precision': 0.30952380952380953, 'recall': 0.3277310924369748, 'f1': 0.31836734693877555, 'number': 119}  | {'precision': 0.769098712446352, 'recall': 0.8413145539906103, 'f1': 0.8035874439461884, 'number': 1065}     | 0.7117            | 0.7938         | 0.7505     | 0.8017           |
 
 
 ### Framework versions

logs/events.out.tfevents.1718870367.HCIDC-SV-DMZ-ORC-NODE02.3859593.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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-size 14915
+oid sha256:bd4a913050d54953d0a52e45810422af9e29ca5479638b40c44dad29b9c5fdab
+size 15984

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:7deb87a23b2a0392f52299c39c4ef3ae054dad426d10c142724ff1f08fb4f2ec
+oid sha256:e0291fb810a4d5867977b06706e2a9e49c98b26ddd2539d5ac2f0393fa9b9990
 size 450558212