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: 0.6782
-- 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
+- Loss: 0.6965
+- Answer: {'precision': 0.7010869565217391, 'recall': 0.7972805933250927, 'f1': 0.746096009253904, 'number': 809}
+- Header: {'precision': 0.3305785123966942, 'recall': 0.33613445378151263, 'f1': 0.33333333333333337, 'number': 119}
+- Question: {'precision': 0.7692307692307693, 'recall': 0.8262910798122066, 'f1': 0.7967406066093254, 'number': 1065}
+- Overall Precision: 0.7162
+- Overall Recall: 0.7852
+- Overall F1: 0.7492
+- Overall Accuracy: 0.8006
 
 ## 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 |
-|:-------------:|:-----:|:----:|:---------------:|:-------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 1.8074        | 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           |
+| Training Loss | Epoch | Step | Validation Loss | Answer                                                                                                         | Header                                                                                                       | Question                                                                                                   | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 1.8343        | 1.0   | 10   | 1.5921          | {'precision': 0.006666666666666667, 'recall': 0.006180469715698393, 'f1': 0.006414368184733804, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                  | {'precision': 0.22067901234567902, 'recall': 0.13427230046948357, 'f1': 0.166958552247519, 'number': 1065} | 0.1059            | 0.0743         | 0.0873     | 0.3510           |
+| 1.4828        | 2.0   | 20   | 1.2849          | {'precision': 0.2738799661876585, 'recall': 0.4004944375772559, 'f1': 0.32530120481927705, 'number': 809}      | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119}                                                  | {'precision': 0.38058114812189936, 'recall': 0.504225352112676, 'f1': 0.43376413570274636, 'number': 1065} | 0.3314            | 0.4320         | 0.3751     | 0.5951           |
+| 1.1444        | 3.0   | 30   | 0.9563          | {'precision': 0.4725897920604915, 'recall': 0.6180469715698393, 'f1': 0.5356186395286556, 'number': 809}       | {'precision': 0.041666666666666664, 'recall': 0.01680672268907563, 'f1': 0.02395209580838323, 'number': 119} | {'precision': 0.5378020265003897, 'recall': 0.647887323943662, 'f1': 0.5877342419080069, 'number': 1065}   | 0.4990            | 0.5981         | 0.5440     | 0.6955           |
+| 0.8658        | 4.0   | 40   | 0.7885          | {'precision': 0.5757009345794393, 'recall': 0.761433868974042, 'f1': 0.6556679084619478, 'number': 809}        | {'precision': 0.1388888888888889, 'recall': 0.08403361344537816, 'f1': 0.10471204188481677, 'number': 119}   | {'precision': 0.6567299006323396, 'recall': 0.6826291079812207, 'f1': 0.6694290976058932, 'number': 1065}  | 0.6016            | 0.6789         | 0.6379     | 0.7601           |
+| 0.6833        | 5.0   | 50   | 0.7124          | {'precision': 0.64375, 'recall': 0.7639060568603214, 'f1': 0.6986998304126625, 'number': 809}                  | {'precision': 0.35, 'recall': 0.23529411764705882, 'f1': 0.28140703517587945, 'number': 119}                 | {'precision': 0.6729354047424366, 'recall': 0.7727699530516432, 'f1': 0.7194055944055944, 'number': 1065}  | 0.6491            | 0.7371         | 0.6903     | 0.7810           |
+| 0.5898        | 6.0   | 60   | 0.6874          | {'precision': 0.6227141482194418, 'recall': 0.799752781211372, 'f1': 0.7002164502164502, 'number': 809}        | {'precision': 0.3411764705882353, 'recall': 0.24369747899159663, 'f1': 0.28431372549019607, 'number': 119}   | {'precision': 0.7236492471213464, 'recall': 0.7671361502347418, 'f1': 0.7447584320875114, 'number': 1065}  | 0.6627            | 0.7491         | 0.7033     | 0.7851           |
+| 0.5126        | 7.0   | 70   | 0.6599          | {'precision': 0.6705632306057385, 'recall': 0.7799752781211372, 'f1': 0.7211428571428572, 'number': 809}       | {'precision': 0.32673267326732675, 'recall': 0.2773109243697479, 'f1': 0.30000000000000004, 'number': 119}   | {'precision': 0.7427821522309711, 'recall': 0.7971830985915493, 'f1': 0.7690217391304347, 'number': 1065}  | 0.6924            | 0.7592         | 0.7243     | 0.7963           |
+| 0.4534        | 8.0   | 80   | 0.6562          | {'precision': 0.670490093847758, 'recall': 0.7948084054388134, 'f1': 0.7273755656108597, 'number': 809}        | {'precision': 0.2966101694915254, 'recall': 0.29411764705882354, 'f1': 0.2953586497890296, 'number': 119}    | {'precision': 0.7476475620188195, 'recall': 0.8206572769953052, 'f1': 0.7824529991047449, 'number': 1065}  | 0.6910            | 0.7787         | 0.7322     | 0.7954           |
+| 0.3984        | 9.0   | 90   | 0.6561          | {'precision': 0.6838709677419355, 'recall': 0.7861557478368356, 'f1': 0.7314548591144335, 'number': 809}       | {'precision': 0.3333333333333333, 'recall': 0.3025210084033613, 'f1': 0.3171806167400881, 'number': 119}     | {'precision': 0.7555555555555555, 'recall': 0.8300469483568075, 'f1': 0.7910514541387024, 'number': 1065}  | 0.7047            | 0.7807         | 0.7408     | 0.7986           |
+| 0.3865        | 10.0  | 100  | 0.6673          | {'precision': 0.6877005347593583, 'recall': 0.7948084054388134, 'f1': 0.7373853211009175, 'number': 809}       | {'precision': 0.31666666666666665, 'recall': 0.31932773109243695, 'f1': 0.3179916317991632, 'number': 119}   | {'precision': 0.7613240418118467, 'recall': 0.8206572769953052, 'f1': 0.7898779936737461, 'number': 1065}  | 0.7059            | 0.7802         | 0.7412     | 0.8019           |
+| 0.3343        | 11.0  | 110  | 0.6761          | {'precision': 0.6853220696937699, 'recall': 0.8022249690976514, 'f1': 0.7391799544419134, 'number': 809}       | {'precision': 0.336283185840708, 'recall': 0.31932773109243695, 'f1': 0.32758620689655166, 'number': 119}    | {'precision': 0.7692307692307693, 'recall': 0.8262910798122066, 'f1': 0.7967406066093254, 'number': 1065}  | 0.7110            | 0.7863         | 0.7467     | 0.7998           |
+| 0.314         | 12.0  | 120  | 0.6772          | {'precision': 0.6989130434782609, 'recall': 0.7948084054388134, 'f1': 0.7437825332562175, 'number': 809}       | {'precision': 0.34545454545454546, 'recall': 0.31932773109243695, 'f1': 0.3318777292576419, 'number': 119}   | {'precision': 0.7698343504795118, 'recall': 0.8291079812206573, 'f1': 0.7983725135623869, 'number': 1065}  | 0.7184            | 0.7847         | 0.7501     | 0.8053           |
+| 0.3008        | 13.0  | 130  | 0.6878          | {'precision': 0.7048648648648649, 'recall': 0.8059332509270705, 'f1': 0.7520184544405998, 'number': 809}       | {'precision': 0.33620689655172414, 'recall': 0.3277310924369748, 'f1': 0.33191489361702126, 'number': 119}   | {'precision': 0.7689594356261023, 'recall': 0.8187793427230047, 'f1': 0.793087767166894, 'number': 1065}   | 0.7186            | 0.7842         | 0.75       | 0.8033           |
+| 0.2797        | 14.0  | 140  | 0.6948          | {'precision': 0.7027322404371584, 'recall': 0.7948084054388134, 'f1': 0.7459396751740139, 'number': 809}       | {'precision': 0.31746031746031744, 'recall': 0.33613445378151263, 'f1': 0.32653061224489793, 'number': 119}  | {'precision': 0.7661996497373029, 'recall': 0.8215962441314554, 'f1': 0.7929315813321249, 'number': 1065}  | 0.7137            | 0.7817         | 0.7462     | 0.8017           |
+| 0.2722        | 15.0  | 150  | 0.6965          | {'precision': 0.7010869565217391, 'recall': 0.7972805933250927, 'f1': 0.746096009253904, 'number': 809}        | {'precision': 0.3305785123966942, 'recall': 0.33613445378151263, 'f1': 0.33333333333333337, 'number': 119}   | {'precision': 0.7692307692307693, 'recall': 0.8262910798122066, 'f1': 0.7967406066093254, 'number': 1065}  | 0.7162            | 0.7852         | 0.7492     | 0.8006           |
 
 
 ### Framework versions

logs/events.out.tfevents.1718871664.HCIDC-SV-DMZ-ORC-NODE02.3873225.6

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a8030a99effe44c8e1ff3bb76785aff08f5c4f6053d336442fa4d4714050ccf4
-size 12783
+oid sha256:bd9a1ee4c04ea79141c13c21a6fb30375e8ac85ff39d561f50b593733c9393bc
+size 15984

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bbedf6278e03eaf8bf912b59b8672d53ae2632229977cfab1255133306c07b19
+oid sha256:407269bdfb61d5284f437311ec92ed06d968ffc4785fba24f120193f68a95329
 size 450558212

tokenizer.json

@@ -1,21 +1,7 @@
 {
   "version": "1.0",
-  "truncation": {
-    "direction": "Right",
-    "max_length": 512,
-    "strategy": "LongestFirst",
-    "stride": 0
-  },
-  "padding": {
-    "strategy": {
-      "Fixed": 512
-    },
-    "direction": "Right",
-    "pad_to_multiple_of": null,
-    "pad_id": 0,
-    "pad_type_id": 0,
-    "pad_token": "[PAD]"
-  },
+  "truncation": null,
+  "padding": null,
   "added_tokens": [
     {
       "id": 0,