End of training

README.md

@@ -1,8 +1,6 @@
 ---
 tags:
 - generated_from_trainer
-datasets:
-- sroie
 model-index:
 - name: layoutlm-sroie
   results: []
@@ -13,17 +11,17 @@ should probably proofread and complete it, then remove this comment. -->
 
 # layoutlm-sroie
 
-This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the sroie dataset.
+This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0320
-- Address: {'precision': 0.9154929577464789, 'recall': 0.9365994236311239, 'f1': 0.925925925925926, 'number': 347}
-- Company: {'precision': 0.9228650137741047, 'recall': 0.9654178674351584, 'f1': 0.9436619718309859, 'number': 347}
-- Date: {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}
-- Total: {'precision': 0.8431372549019608, 'recall': 0.8674351585014409, 'f1': 0.8551136363636365, 'number': 347}
-- Overall Precision: 0.9170
-- Overall Recall: 0.9388
-- Overall F1: 0.9277
-- Overall Accuracy: 0.9942
+- Loss: 0.0325
+- Address: {'precision': 0.9044943820224719, 'recall': 0.9279538904899135, 'f1': 0.9160739687055477, 'number': 347}
+- Company: {'precision': 0.9196675900277008, 'recall': 0.9567723342939481, 'f1': 0.9378531073446328, 'number': 347}
+- Date: {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}
+- Total: {'precision': 0.8913649025069638, 'recall': 0.9221902017291066, 'f1': 0.9065155807365438, 'number': 347}
+- Overall Precision: 0.9242
+- Overall Recall: 0.9488
+- Overall F1: 0.9364
+- Overall Accuracy: 0.9947
 
 ## Model description
 
@@ -52,23 +50,23 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Address                                                                                                  | Company                                                                                                  | Date                                                                                                     | Total                                                                                                      | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
-|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
-| 0.5392        | 1.0   | 40   | 0.1200          | {'precision': 0.8346883468834688, 'recall': 0.8876080691642652, 'f1': 0.8603351955307261, 'number': 347} | {'precision': 0.75, 'recall': 0.8126801152737753, 'f1': 0.7800829875518672, 'number': 347}               | {'precision': 0.648068669527897, 'recall': 0.8703170028818443, 'f1': 0.7429274292742927, 'number': 347}  | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 347}                                                | 0.7366            | 0.6427         | 0.6864     | 0.9712           |
-| 0.0803        | 2.0   | 80   | 0.0485          | {'precision': 0.896358543417367, 'recall': 0.9221902017291066, 'f1': 0.9090909090909091, 'number': 347}  | {'precision': 0.8897849462365591, 'recall': 0.9538904899135446, 'f1': 0.9207232267037552, 'number': 347} | {'precision': 0.9628571428571429, 'recall': 0.9711815561959655, 'f1': 0.9670014347202295, 'number': 347} | {'precision': 0.5219298245614035, 'recall': 0.34293948126801155, 'f1': 0.41391304347826086, 'number': 347} | 0.8470            | 0.7976         | 0.8215     | 0.9876           |
-| 0.0441        | 3.0   | 120  | 0.0373          | {'precision': 0.9131652661064426, 'recall': 0.9394812680115274, 'f1': 0.9261363636363636, 'number': 347} | {'precision': 0.9277777777777778, 'recall': 0.962536023054755, 'f1': 0.9448373408769449, 'number': 347}  | {'precision': 0.9826589595375722, 'recall': 0.9798270893371758, 'f1': 0.9812409812409811, 'number': 347} | {'precision': 0.5418502202643172, 'recall': 0.7089337175792507, 'f1': 0.6142322097378278, 'number': 347}   | 0.8214            | 0.8977         | 0.8578     | 0.9897           |
-| 0.0309        | 4.0   | 160  | 0.0333          | {'precision': 0.8864265927977839, 'recall': 0.9221902017291066, 'f1': 0.903954802259887, 'number': 347}  | {'precision': 0.915068493150685, 'recall': 0.962536023054755, 'f1': 0.9382022471910113, 'number': 347}   | {'precision': 0.9912790697674418, 'recall': 0.9827089337175793, 'f1': 0.9869753979739508, 'number': 347} | {'precision': 0.6556122448979592, 'recall': 0.7406340057636888, 'f1': 0.6955345060893099, 'number': 347}   | 0.8564            | 0.9020         | 0.8786     | 0.9916           |
-| 0.0249        | 5.0   | 200  | 0.0318          | {'precision': 0.907563025210084, 'recall': 0.9337175792507204, 'f1': 0.9204545454545455, 'number': 347}  | {'precision': 0.9054054054054054, 'recall': 0.9654178674351584, 'f1': 0.9344490934449093, 'number': 347} | {'precision': 0.9912536443148688, 'recall': 0.9798270893371758, 'f1': 0.9855072463768115, 'number': 347} | {'precision': 0.7186700767263428, 'recall': 0.8097982708933718, 'f1': 0.7615176151761518, 'number': 347}   | 0.8761            | 0.9222         | 0.8986     | 0.9924           |
-| 0.0183        | 6.0   | 240  | 0.0294          | {'precision': 0.9103641456582633, 'recall': 0.9365994236311239, 'f1': 0.9232954545454545, 'number': 347} | {'precision': 0.9201101928374655, 'recall': 0.962536023054755, 'f1': 0.9408450704225352, 'number': 347}  | {'precision': 0.991304347826087, 'recall': 0.9855907780979827, 'f1': 0.9884393063583815, 'number': 347}  | {'precision': 0.8397435897435898, 'recall': 0.7550432276657061, 'f1': 0.795144157814871, 'number': 347}    | 0.9172            | 0.9099         | 0.9136     | 0.9936           |
-| 0.0155        | 7.0   | 280  | 0.0290          | {'precision': 0.9129213483146067, 'recall': 0.9365994236311239, 'f1': 0.9246088193456615, 'number': 347} | {'precision': 0.9155313351498637, 'recall': 0.968299711815562, 'f1': 0.9411764705882353, 'number': 347}  | {'precision': 0.9855907780979827, 'recall': 0.9855907780979827, 'f1': 0.9855907780979827, 'number': 347} | {'precision': 0.8228882833787466, 'recall': 0.8703170028818443, 'f1': 0.8459383753501399, 'number': 347}   | 0.9081            | 0.9402         | 0.9239     | 0.9940           |
-| 0.0125        | 8.0   | 320  | 0.0322          | {'precision': 0.9103641456582633, 'recall': 0.9365994236311239, 'f1': 0.9232954545454545, 'number': 347} | {'precision': 0.9027027027027027, 'recall': 0.962536023054755, 'f1': 0.9316596931659692, 'number': 347}  | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8269230769230769, 'recall': 0.8674351585014409, 'f1': 0.8466947960618847, 'number': 347}   | 0.9061            | 0.9380         | 0.9218     | 0.9936           |
-| 0.0108        | 9.0   | 360  | 0.0302          | {'precision': 0.9078212290502793, 'recall': 0.9365994236311239, 'f1': 0.921985815602837, 'number': 347}  | {'precision': 0.9205479452054794, 'recall': 0.968299711815562, 'f1': 0.9438202247191011, 'number': 347}  | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8386167146974063, 'recall': 0.8386167146974063, 'f1': 0.8386167146974063, 'number': 347}   | 0.9138            | 0.9323         | 0.9230     | 0.9941           |
-| 0.0099        | 10.0  | 400  | 0.0304          | {'precision': 0.8833333333333333, 'recall': 0.9164265129682997, 'f1': 0.8995756718528995, 'number': 347} | {'precision': 0.9226519337016574, 'recall': 0.962536023054755, 'f1': 0.9421720733427363, 'number': 347}  | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8472222222222222, 'recall': 0.8789625360230547, 'f1': 0.8628005657708628, 'number': 347}   | 0.9097            | 0.9359         | 0.9226     | 0.9943           |
-| 0.0079        | 11.0  | 440  | 0.0312          | {'precision': 0.9206798866855525, 'recall': 0.9365994236311239, 'f1': 0.9285714285714285, 'number': 347} | {'precision': 0.9203296703296703, 'recall': 0.9654178674351584, 'f1': 0.9423347398030942, 'number': 347} | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8515406162464986, 'recall': 0.8760806916426513, 'f1': 0.8636363636363638, 'number': 347}   | 0.9197            | 0.9409         | 0.9302     | 0.9945           |
-| 0.0079        | 12.0  | 480  | 0.0322          | {'precision': 0.9101123595505618, 'recall': 0.9337175792507204, 'f1': 0.9217638691322901, 'number': 347} | {'precision': 0.9153005464480874, 'recall': 0.9654178674351584, 'f1': 0.9396914446002805, 'number': 347} | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8310626702997275, 'recall': 0.8789625360230547, 'f1': 0.8543417366946778, 'number': 347}   | 0.9101            | 0.9409         | 0.9253     | 0.9941           |
-| 0.0068        | 13.0  | 520  | 0.0311          | {'precision': 0.9101123595505618, 'recall': 0.9337175792507204, 'f1': 0.9217638691322901, 'number': 347} | {'precision': 0.9226519337016574, 'recall': 0.962536023054755, 'f1': 0.9421720733427363, 'number': 347}  | {'precision': 0.991304347826087, 'recall': 0.9855907780979827, 'f1': 0.9884393063583815, 'number': 347}  | {'precision': 0.8467966573816156, 'recall': 0.8760806916426513, 'f1': 0.8611898016997168, 'number': 347}   | 0.9170            | 0.9395         | 0.9281     | 0.9943           |
-| 0.0068        | 14.0  | 560  | 0.0318          | {'precision': 0.9101123595505618, 'recall': 0.9337175792507204, 'f1': 0.9217638691322901, 'number': 347} | {'precision': 0.9201101928374655, 'recall': 0.962536023054755, 'f1': 0.9408450704225352, 'number': 347}  | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.837465564738292, 'recall': 0.8760806916426513, 'f1': 0.8563380281690142, 'number': 347}    | 0.9132            | 0.9395         | 0.9261     | 0.9943           |
-| 0.0061        | 15.0  | 600  | 0.0320          | {'precision': 0.9154929577464789, 'recall': 0.9365994236311239, 'f1': 0.925925925925926, 'number': 347}  | {'precision': 0.9228650137741047, 'recall': 0.9654178674351584, 'f1': 0.9436619718309859, 'number': 347} | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8431372549019608, 'recall': 0.8674351585014409, 'f1': 0.8551136363636365, 'number': 347}   | 0.9170            | 0.9388         | 0.9277     | 0.9942           |
+| Training Loss | Epoch | Step | Validation Loss | Address                                                                                                  | Company                                                                                                  | Date                                                                                                     | Total                                                                                                    | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
+| 0.4787        | 1.0   | 40   | 0.1051          | {'precision': 0.8115183246073299, 'recall': 0.8933717579250721, 'f1': 0.850480109739369, 'number': 347}  | {'precision': 0.6813725490196079, 'recall': 0.8011527377521613, 'f1': 0.7364238410596026, 'number': 347} | {'precision': 0.7438423645320197, 'recall': 0.8703170028818443, 'f1': 0.8021248339973439, 'number': 347} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 347}                                              | 0.7441            | 0.6412         | 0.6889     | 0.9705           |
+| 0.0698        | 2.0   | 80   | 0.0453          | {'precision': 0.848, 'recall': 0.9164265129682997, 'f1': 0.8808864265927978, 'number': 347}              | {'precision': 0.8080808080808081, 'recall': 0.9221902017291066, 'f1': 0.8613728129205921, 'number': 347} | {'precision': 0.9281767955801105, 'recall': 0.968299711815562, 'f1': 0.9478138222849083, 'number': 347}  | {'precision': 0.6992481203007519, 'recall': 0.8040345821325648, 'f1': 0.7479892761394101, 'number': 347} | 0.8179            | 0.9027         | 0.8582     | 0.9882           |
+| 0.0326        | 3.0   | 120  | 0.0317          | {'precision': 0.8763736263736264, 'recall': 0.9193083573487032, 'f1': 0.8973277074542897, 'number': 347} | {'precision': 0.888283378746594, 'recall': 0.9394812680115274, 'f1': 0.9131652661064427, 'number': 347}  | {'precision': 0.9713467048710601, 'recall': 0.9769452449567724, 'f1': 0.9741379310344828, 'number': 347} | {'precision': 0.8259668508287292, 'recall': 0.861671469740634, 'f1': 0.8434414668547249, 'number': 347}  | 0.8897            | 0.9244         | 0.9067     | 0.9928           |
+| 0.0222        | 4.0   | 160  | 0.0333          | {'precision': 0.8922651933701657, 'recall': 0.930835734870317, 'f1': 0.9111424541607898, 'number': 347}  | {'precision': 0.8983516483516484, 'recall': 0.9423631123919308, 'f1': 0.919831223628692, 'number': 347}  | {'precision': 0.9912280701754386, 'recall': 0.9769452449567724, 'f1': 0.9840348330914369, 'number': 347} | {'precision': 0.7348837209302326, 'recall': 0.9106628242074928, 'f1': 0.8133848133848134, 'number': 347} | 0.8712            | 0.9402         | 0.9044     | 0.9921           |
+| 0.0185        | 5.0   | 200  | 0.0288          | {'precision': 0.9209039548022598, 'recall': 0.9394812680115274, 'f1': 0.9300998573466476, 'number': 347} | {'precision': 0.8856382978723404, 'recall': 0.9596541786743515, 'f1': 0.921161825726141, 'number': 347}  | {'precision': 0.991304347826087, 'recall': 0.9855907780979827, 'f1': 0.9884393063583815, 'number': 347}  | {'precision': 0.8547945205479452, 'recall': 0.899135446685879, 'f1': 0.8764044943820225, 'number': 347}  | 0.9118            | 0.9460         | 0.9286     | 0.9938           |
+| 0.0141        | 6.0   | 240  | 0.0269          | {'precision': 0.8991596638655462, 'recall': 0.9250720461095101, 'f1': 0.9119318181818182, 'number': 347} | {'precision': 0.9108635097493036, 'recall': 0.9423631123919308, 'f1': 0.926345609065156, 'number': 347}  | {'precision': 0.9884393063583815, 'recall': 0.9855907780979827, 'f1': 0.987012987012987, 'number': 347}  | {'precision': 0.8795518207282913, 'recall': 0.9048991354466859, 'f1': 0.8920454545454546, 'number': 347} | 0.9190            | 0.9395         | 0.9291     | 0.9944           |
+| 0.0117        | 7.0   | 280  | 0.0281          | {'precision': 0.9178470254957507, 'recall': 0.9337175792507204, 'f1': 0.9257142857142857, 'number': 347} | {'precision': 0.9138888888888889, 'recall': 0.9481268011527377, 'f1': 0.9306930693069307, 'number': 347} | {'precision': 0.9855907780979827, 'recall': 0.9855907780979827, 'f1': 0.9855907780979827, 'number': 347} | {'precision': 0.8985507246376812, 'recall': 0.8933717579250721, 'f1': 0.8959537572254335, 'number': 347} | 0.9288            | 0.9402         | 0.9345     | 0.9945           |
+| 0.0104        | 8.0   | 320  | 0.0313          | {'precision': 0.9101123595505618, 'recall': 0.9337175792507204, 'f1': 0.9217638691322901, 'number': 347} | {'precision': 0.9043715846994536, 'recall': 0.9538904899135446, 'f1': 0.9284712482468442, 'number': 347} | {'precision': 0.9717514124293786, 'recall': 0.9913544668587896, 'f1': 0.9814550641940086, 'number': 347} | {'precision': 0.868632707774799, 'recall': 0.9337175792507204, 'f1': 0.8999999999999999, 'number': 347}  | 0.9130            | 0.9532         | 0.9327     | 0.9941           |
+| 0.009         | 9.0   | 360  | 0.0282          | {'precision': 0.9204545454545454, 'recall': 0.9337175792507204, 'f1': 0.927038626609442, 'number': 347}  | {'precision': 0.9171270718232044, 'recall': 0.9567723342939481, 'f1': 0.9365303244005642, 'number': 347} | {'precision': 0.9828571428571429, 'recall': 0.9913544668587896, 'f1': 0.9870875179340028, 'number': 347} | {'precision': 0.8885793871866295, 'recall': 0.9193083573487032, 'f1': 0.9036827195467422, 'number': 347} | 0.9269            | 0.9503         | 0.9385     | 0.9949           |
+| 0.0081        | 10.0  | 400  | 0.0313          | {'precision': 0.9047619047619048, 'recall': 0.930835734870317, 'f1': 0.9176136363636365, 'number': 347}  | {'precision': 0.9217877094972067, 'recall': 0.9510086455331412, 'f1': 0.9361702127659575, 'number': 347} | {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}  | {'precision': 0.8974358974358975, 'recall': 0.9077809798270894, 'f1': 0.9025787965616047, 'number': 347} | 0.9265            | 0.9445         | 0.9354     | 0.9945           |
+| 0.0064        | 11.0  | 440  | 0.0318          | {'precision': 0.9047619047619048, 'recall': 0.930835734870317, 'f1': 0.9176136363636365, 'number': 347}  | {'precision': 0.9138888888888889, 'recall': 0.9481268011527377, 'f1': 0.9306930693069307, 'number': 347} | {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}  | {'precision': 0.8791208791208791, 'recall': 0.9221902017291066, 'f1': 0.90014064697609, 'number': 347}   | 0.9196            | 0.9474         | 0.9333     | 0.9944           |
+| 0.0063        | 12.0  | 480  | 0.0335          | {'precision': 0.8994413407821229, 'recall': 0.9279538904899135, 'f1': 0.9134751773049646, 'number': 347} | {'precision': 0.9088397790055248, 'recall': 0.9481268011527377, 'f1': 0.928067700987306, 'number': 347}  | {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}  | {'precision': 0.8839779005524862, 'recall': 0.9221902017291066, 'f1': 0.9026798307475318, 'number': 347} | 0.9182            | 0.9467         | 0.9322     | 0.9943           |
+| 0.0054        | 13.0  | 520  | 0.0312          | {'precision': 0.9070422535211268, 'recall': 0.9279538904899135, 'f1': 0.9173789173789173, 'number': 347} | {'precision': 0.9194444444444444, 'recall': 0.9538904899135446, 'f1': 0.9363507779349363, 'number': 347} | {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}  | {'precision': 0.8839779005524862, 'recall': 0.9221902017291066, 'f1': 0.9026798307475318, 'number': 347} | 0.9229            | 0.9481         | 0.9353     | 0.9947           |
+| 0.0054        | 14.0  | 560  | 0.0326          | {'precision': 0.9044943820224719, 'recall': 0.9279538904899135, 'f1': 0.9160739687055477, 'number': 347} | {'precision': 0.9222222222222223, 'recall': 0.9567723342939481, 'f1': 0.9391796322489392, 'number': 347} | {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}  | {'precision': 0.8910614525139665, 'recall': 0.9193083573487032, 'f1': 0.9049645390070922, 'number': 347} | 0.9248            | 0.9481         | 0.9363     | 0.9946           |
+| 0.0048        | 15.0  | 600  | 0.0325          | {'precision': 0.9044943820224719, 'recall': 0.9279538904899135, 'f1': 0.9160739687055477, 'number': 347} | {'precision': 0.9196675900277008, 'recall': 0.9567723342939481, 'f1': 0.9378531073446328, 'number': 347} | {'precision': 0.9828080229226361, 'recall': 0.9884726224783862, 'f1': 0.985632183908046, 'number': 347}  | {'precision': 0.8913649025069638, 'recall': 0.9221902017291066, 'f1': 0.9065155807365438, 'number': 347} | 0.9242            | 0.9488         | 0.9364     | 0.9947           |
 
 
 ### Framework versions

logs/events.out.tfevents.1700674111.7c58e45ee39e.832.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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