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layoutlm-funsd

Token Classification
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layoutlm
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  1. README.md +61 -41
  2. logs/events.out.tfevents.1710848341.debb6005789e.10976.0 +2 -2
  3. model.safetensors +1 -1
  4. tokenizer.json +16 -2
README.md CHANGED
@@ -17,14 +17,14 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4247
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- - Answer: {'precision': 0.46065259117082535, 'recall': 0.5933250927070457, 'f1': 0.5186385737439222, 'number': 809}
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- - Header: {'precision': 0.2692307692307692, 'recall': 0.29411764705882354, 'f1': 0.28112449799196787, 'number': 119}
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- - Question: {'precision': 0.5629754860524091, 'recall': 0.6253521126760564, 'f1': 0.5925266903914591, 'number': 1065}
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- - Overall Precision: 0.5015
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- - Overall Recall: 0.5926
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- - Overall F1: 0.5432
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- - Overall Accuracy: 0.6236
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  ## Model description
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@@ -49,42 +49,62 @@ The following hyperparameters were used during training:
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 30
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------:|:-------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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- | 1.719 | 1.0 | 10 | 1.5186 | {'precision': 0.05500550055005501, 'recall': 0.06180469715698393, 'f1': 0.058207217694994186, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.24500907441016334, 'recall': 0.2535211267605634, 'f1': 0.24919243193354867, 'number': 1065} | 0.1591 | 0.1606 | 0.1598 | 0.3513 |
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- | 1.4217 | 2.0 | 20 | 1.3567 | {'precision': 0.22399150743099788, 'recall': 0.5216316440049443, 'f1': 0.31340512439658375, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.27875793930839804, 'recall': 0.37089201877934275, 'f1': 0.3182917002417405, 'number': 1065} | 0.2475 | 0.4099 | 0.3087 | 0.4226 |
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- | 1.2866 | 3.0 | 30 | 1.2513 | {'precision': 0.25821287779237845, 'recall': 0.4857849196538937, 'f1': 0.3371943371943372, 'number': 809} | {'precision': 0.02564102564102564, 'recall': 0.008403361344537815, 'f1': 0.012658227848101267, 'number': 119} | {'precision': 0.353081986834231, 'recall': 0.5539906103286385, 'f1': 0.43128654970760233, 'number': 1065} | 0.3045 | 0.4937 | 0.3767 | 0.4816 |
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- | 1.1552 | 4.0 | 40 | 1.1240 | {'precision': 0.2970859985785359, 'recall': 0.5166872682323856, 'f1': 0.37725631768953066, 'number': 809} | {'precision': 0.26595744680851063, 'recall': 0.21008403361344538, 'f1': 0.23474178403755866, 'number': 119} | {'precision': 0.40802213001383125, 'recall': 0.5539906103286385, 'f1': 0.46993229788928714, 'number': 1065} | 0.3505 | 0.5183 | 0.4182 | 0.5663 |
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- | 1.0315 | 5.0 | 50 | 1.1886 | {'precision': 0.33358490566037735, 'recall': 0.546353522867738, 'f1': 0.41424554826616683, 'number': 809} | {'precision': 0.25675675675675674, 'recall': 0.15966386554621848, 'f1': 0.19689119170984457, 'number': 119} | {'precision': 0.4381443298969072, 'recall': 0.5586854460093896, 'f1': 0.49112670243499795, 'number': 1065} | 0.3830 | 0.5299 | 0.4446 | 0.5518 |
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- | 0.9523 | 6.0 | 60 | 1.1240 | {'precision': 0.35634743875278396, 'recall': 0.5933250927070457, 'f1': 0.4452690166975881, 'number': 809} | {'precision': 0.2558139534883721, 'recall': 0.18487394957983194, 'f1': 0.21463414634146344, 'number': 119} | {'precision': 0.48498233215547704, 'recall': 0.5154929577464789, 'f1': 0.49977241693218016, 'number': 1065} | 0.4097 | 0.5273 | 0.4612 | 0.5936 |
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- | 0.8561 | 7.0 | 70 | 1.0766 | {'precision': 0.37615449202350965, 'recall': 0.553770086526576, 'f1': 0.448, 'number': 809} | {'precision': 0.2857142857142857, 'recall': 0.20168067226890757, 'f1': 0.23645320197044337, 'number': 119} | {'precision': 0.49523052464228934, 'recall': 0.5849765258215962, 'f1': 0.5363753766681015, 'number': 1065} | 0.4323 | 0.5494 | 0.4839 | 0.6072 |
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- | 0.7862 | 8.0 | 80 | 1.0865 | {'precision': 0.39285714285714285, 'recall': 0.4894932014833127, 'f1': 0.43588332416070447, 'number': 809} | {'precision': 0.31683168316831684, 'recall': 0.2689075630252101, 'f1': 0.29090909090909095, 'number': 119} | {'precision': 0.4698713608666215, 'recall': 0.6516431924882629, 'f1': 0.5460267505900864, 'number': 1065} | 0.4339 | 0.5630 | 0.4901 | 0.6163 |
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- | 0.7272 | 9.0 | 90 | 1.1819 | {'precision': 0.37337413925019125, 'recall': 0.6032138442521632, 'f1': 0.46124763705103966, 'number': 809} | {'precision': 0.3023255813953488, 'recall': 0.2184873949579832, 'f1': 0.25365853658536586, 'number': 119} | {'precision': 0.5397676496872207, 'recall': 0.5671361502347417, 'f1': 0.553113553113553, 'number': 1065} | 0.4451 | 0.5610 | 0.4963 | 0.6082 |
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- | 0.7468 | 10.0 | 100 | 1.2023 | {'precision': 0.3776325344952796, 'recall': 0.6427688504326329, 'f1': 0.4757548032936871, 'number': 809} | {'precision': 0.3076923076923077, 'recall': 0.23529411764705882, 'f1': 0.26666666666666666, 'number': 119} | {'precision': 0.5464015151515151, 'recall': 0.5417840375586854, 'f1': 0.5440829797265442, 'number': 1065} | 0.4457 | 0.5645 | 0.4981 | 0.6125 |
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- | 0.6407 | 11.0 | 110 | 1.1119 | {'precision': 0.41081081081081083, 'recall': 0.5636588380716935, 'f1': 0.4752475247524753, 'number': 809} | {'precision': 0.3153153153153153, 'recall': 0.29411764705882354, 'f1': 0.30434782608695654, 'number': 119} | {'precision': 0.5374787052810903, 'recall': 0.5924882629107981, 'f1': 0.5636444841447075, 'number': 1065} | 0.4685 | 0.5630 | 0.5114 | 0.6186 |
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- | 0.6276 | 12.0 | 120 | 1.1499 | {'precision': 0.4605855855855856, 'recall': 0.5055624227441285, 'f1': 0.48202710665880966, 'number': 809} | {'precision': 0.3217391304347826, 'recall': 0.31092436974789917, 'f1': 0.3162393162393162, 'number': 119} | {'precision': 0.5130813953488372, 'recall': 0.6629107981220658, 'f1': 0.5784514543219992, 'number': 1065} | 0.4842 | 0.5780 | 0.5270 | 0.6045 |
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- | 0.5603 | 13.0 | 130 | 1.1774 | {'precision': 0.43646408839779005, 'recall': 0.5859085290482077, 'f1': 0.5002638522427441, 'number': 809} | {'precision': 0.2608695652173913, 'recall': 0.3025210084033613, 'f1': 0.28015564202334625, 'number': 119} | {'precision': 0.543313708999159, 'recall': 0.6065727699530516, 'f1': 0.5732031943212067, 'number': 1065} | 0.4791 | 0.5800 | 0.5247 | 0.6247 |
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- | 0.5174 | 14.0 | 140 | 1.1518 | {'precision': 0.4443266171792153, 'recall': 0.5179233621755254, 'f1': 0.478310502283105, 'number': 809} | {'precision': 0.288, 'recall': 0.3025210084033613, 'f1': 0.2950819672131147, 'number': 119} | {'precision': 0.511794138670479, 'recall': 0.672300469483568, 'f1': 0.5811688311688311, 'number': 1065} | 0.4747 | 0.5876 | 0.5251 | 0.6275 |
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- | 0.4984 | 15.0 | 150 | 1.2622 | {'precision': 0.4340309372156506, 'recall': 0.5896168108776267, 'f1': 0.5000000000000001, 'number': 809} | {'precision': 0.28695652173913044, 'recall': 0.2773109243697479, 'f1': 0.2820512820512821, 'number': 119} | {'precision': 0.5659722222222222, 'recall': 0.612206572769953, 'f1': 0.5881822282363555, 'number': 1065} | 0.4911 | 0.5830 | 0.5331 | 0.6283 |
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- | 0.4717 | 16.0 | 160 | 1.2309 | {'precision': 0.4291996481970097, 'recall': 0.6032138442521632, 'f1': 0.5015416238437822, 'number': 809} | {'precision': 0.288135593220339, 'recall': 0.2857142857142857, 'f1': 0.2869198312236287, 'number': 119} | {'precision': 0.5609756097560976, 'recall': 0.5615023474178403, 'f1': 0.5612388549976538, 'number': 1065} | 0.4826 | 0.5620 | 0.5192 | 0.6214 |
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- | 0.4414 | 17.0 | 170 | 1.2624 | {'precision': 0.4625984251968504, 'recall': 0.580964153275649, 'f1': 0.515068493150685, 'number': 809} | {'precision': 0.30578512396694213, 'recall': 0.31092436974789917, 'f1': 0.30833333333333335, 'number': 119} | {'precision': 0.5645295587010825, 'recall': 0.6366197183098592, 'f1': 0.5984112974404237, 'number': 1065} | 0.5068 | 0.5946 | 0.5472 | 0.6218 |
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- | 0.4089 | 18.0 | 180 | 1.2731 | {'precision': 0.4601226993865031, 'recall': 0.5562422744128553, 'f1': 0.5036373810856184, 'number': 809} | {'precision': 0.3302752293577982, 'recall': 0.3025210084033613, 'f1': 0.31578947368421045, 'number': 119} | {'precision': 0.5450310559006211, 'recall': 0.6591549295774648, 'f1': 0.5966850828729281, 'number': 1065} | 0.5002 | 0.5961 | 0.5440 | 0.6207 |
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- | 0.4123 | 19.0 | 190 | 1.3471 | {'precision': 0.45244956772334294, 'recall': 0.5822002472187886, 'f1': 0.5091891891891892, 'number': 809} | {'precision': 0.3177570093457944, 'recall': 0.2857142857142857, 'f1': 0.3008849557522124, 'number': 119} | {'precision': 0.5504511894995898, 'recall': 0.6300469483568075, 'f1': 0.5875656742556917, 'number': 1065} | 0.4968 | 0.5901 | 0.5394 | 0.6099 |
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- | 0.3827 | 20.0 | 200 | 1.3405 | {'precision': 0.4388888888888889, 'recall': 0.5859085290482077, 'f1': 0.5018528321863421, 'number': 809} | {'precision': 0.2734375, 'recall': 0.29411764705882354, 'f1': 0.2834008097165992, 'number': 119} | {'precision': 0.5659246575342466, 'recall': 0.6206572769953052, 'f1': 0.5920286609941782, 'number': 1065} | 0.4924 | 0.5871 | 0.5356 | 0.6150 |
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- | 0.3578 | 21.0 | 210 | 1.3585 | {'precision': 0.4352189781021898, 'recall': 0.5896168108776267, 'f1': 0.5007874015748032, 'number': 809} | {'precision': 0.28688524590163933, 'recall': 0.29411764705882354, 'f1': 0.2904564315352697, 'number': 119} | {'precision': 0.5677590788308238, 'recall': 0.6018779342723005, 'f1': 0.5843208751139473, 'number': 1065} | 0.4913 | 0.5785 | 0.5313 | 0.6173 |
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- | 0.3672 | 22.0 | 220 | 1.4072 | {'precision': 0.4651866801210898, 'recall': 0.5698393077873919, 'f1': 0.5122222222222222, 'number': 809} | {'precision': 0.26865671641791045, 'recall': 0.3025210084033613, 'f1': 0.2845849802371542, 'number': 119} | {'precision': 0.5686106346483705, 'recall': 0.6225352112676056, 'f1': 0.5943523083818915, 'number': 1065} | 0.5063 | 0.5820 | 0.5415 | 0.6134 |
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- | 0.3256 | 23.0 | 230 | 1.3906 | {'precision': 0.4444444444444444, 'recall': 0.5587144622991347, 'f1': 0.49507119386637455, 'number': 809} | {'precision': 0.25517241379310346, 'recall': 0.31092436974789917, 'f1': 0.2803030303030303, 'number': 119} | {'precision': 0.5697177074422584, 'recall': 0.6253521126760564, 'f1': 0.5962399283795882, 'number': 1065} | 0.4955 | 0.5795 | 0.5342 | 0.6059 |
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- | 0.3257 | 24.0 | 240 | 1.3932 | {'precision': 0.43564356435643564, 'recall': 0.5982694684796045, 'f1': 0.5041666666666667, 'number': 809} | {'precision': 0.2647058823529412, 'recall': 0.3025210084033613, 'f1': 0.2823529411764706, 'number': 119} | {'precision': 0.5610589239965841, 'recall': 0.6169014084507042, 'f1': 0.5876565295169945, 'number': 1065} | 0.4868 | 0.5906 | 0.5337 | 0.6099 |
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- | 0.3225 | 25.0 | 250 | 1.4026 | {'precision': 0.45896946564885494, 'recall': 0.5945611866501854, 'f1': 0.5180398492191707, 'number': 809} | {'precision': 0.2882882882882883, 'recall': 0.2689075630252101, 'f1': 0.2782608695652174, 'number': 119} | {'precision': 0.5693739424703892, 'recall': 0.631924882629108, 'f1': 0.5990209167779261, 'number': 1065} | 0.5066 | 0.5951 | 0.5473 | 0.6240 |
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- | 0.317 | 26.0 | 260 | 1.4381 | {'precision': 0.46397694524495675, 'recall': 0.5970333745364648, 'f1': 0.5221621621621622, 'number': 809} | {'precision': 0.28225806451612906, 'recall': 0.29411764705882354, 'f1': 0.2880658436213992, 'number': 119} | {'precision': 0.5862377122430742, 'recall': 0.615962441314554, 'f1': 0.6007326007326007, 'number': 1065} | 0.5140 | 0.5891 | 0.5490 | 0.6146 |
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- | 0.3098 | 27.0 | 270 | 1.4192 | {'precision': 0.46586345381526106, 'recall': 0.5735475896168108, 'f1': 0.5141274238227146, 'number': 809} | {'precision': 0.25735294117647056, 'recall': 0.29411764705882354, 'f1': 0.2745098039215686, 'number': 119} | {'precision': 0.5634146341463414, 'recall': 0.6507042253521127, 'f1': 0.6039215686274508, 'number': 1065} | 0.5047 | 0.5981 | 0.5474 | 0.6193 |
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- | 0.3038 | 28.0 | 280 | 1.4316 | {'precision': 0.4594078319006686, 'recall': 0.5945611866501854, 'f1': 0.5183189655172413, 'number': 809} | {'precision': 0.26515151515151514, 'recall': 0.29411764705882354, 'f1': 0.2788844621513944, 'number': 119} | {'precision': 0.5786163522012578, 'recall': 0.6046948356807512, 'f1': 0.5913682277318641, 'number': 1065} | 0.5061 | 0.5820 | 0.5414 | 0.6198 |
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- | 0.2984 | 29.0 | 290 | 1.4212 | {'precision': 0.45687203791469194, 'recall': 0.595797280593325, 'f1': 0.5171673819742489, 'number': 809} | {'precision': 0.2734375, 'recall': 0.29411764705882354, 'f1': 0.2834008097165992, 'number': 119} | {'precision': 0.5619694397283531, 'recall': 0.6215962441314554, 'f1': 0.5902808738296924, 'number': 1065} | 0.4994 | 0.5916 | 0.5416 | 0.6239 |
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- | 0.2937 | 30.0 | 300 | 1.4247 | {'precision': 0.46065259117082535, 'recall': 0.5933250927070457, 'f1': 0.5186385737439222, 'number': 809} | {'precision': 0.2692307692307692, 'recall': 0.29411764705882354, 'f1': 0.28112449799196787, 'number': 119} | {'precision': 0.5629754860524091, 'recall': 0.6253521126760564, 'f1': 0.5925266903914591, 'number': 1065} | 0.5015 | 0.5926 | 0.5432 | 0.6236 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
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18
  This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the funsd dataset.
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  It achieves the following results on the evaluation set:
20
+ - Loss: 1.6784
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+ - Answer: {'precision': 0.4630541871921182, 'recall': 0.580964153275649, 'f1': 0.5153508771929824, 'number': 809}
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+ - Header: {'precision': 0.4470588235294118, 'recall': 0.31932773109243695, 'f1': 0.37254901960784315, 'number': 119}
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+ - Question: {'precision': 0.5822259136212624, 'recall': 0.6582159624413145, 'f1': 0.617893345085941, 'number': 1065}
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+ - Overall Precision: 0.5247
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+ - Overall Recall: 0.6066
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+ - Overall F1: 0.5627
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+ - Overall Accuracy: 0.6411
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29
  ## Model description
30
 
 
49
  - seed: 42
50
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
  - lr_scheduler_type: linear
52
+ - num_epochs: 50
53
 
54
  ### Training results
55
 
56
+ | Training Loss | Epoch | Step | Validation Loss | Answer | Header | Question | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
57
+ |:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 1.7288 | 1.0 | 10 | 1.5435 | {'precision': 0.022058823529411766, 'recall': 0.014833127317676144, 'f1': 0.017738359201773836, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.19180633147113593, 'recall': 0.09671361502347418, 'f1': 0.1285892634207241, 'number': 1065} | 0.1064 | 0.0577 | 0.0748 | 0.3266 |
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+ | 1.4353 | 2.0 | 20 | 1.3528 | {'precision': 0.20369301788805538, 'recall': 0.4363411619283066, 'f1': 0.27773406766325726, 'number': 809} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 119} | {'precision': 0.2926481084939329, 'recall': 0.38497652582159625, 'f1': 0.33252230332522303, 'number': 1065} | 0.2427 | 0.3828 | 0.2971 | 0.4262 |
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+ | 1.2751 | 3.0 | 30 | 1.2397 | {'precision': 0.24175084175084174, 'recall': 0.4437577255871446, 'f1': 0.3129904097646033, 'number': 809} | {'precision': 0.03636363636363636, 'recall': 0.01680672268907563, 'f1': 0.022988505747126436, 'number': 119} | {'precision': 0.34423076923076923, 'recall': 0.504225352112676, 'f1': 0.40914285714285714, 'number': 1065} | 0.2897 | 0.4506 | 0.3526 | 0.4736 |
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+ | 1.1382 | 4.0 | 40 | 1.1096 | {'precision': 0.2822349570200573, 'recall': 0.48702101359703337, 'f1': 0.3573696145124716, 'number': 809} | {'precision': 0.2111111111111111, 'recall': 0.15966386554621848, 'f1': 0.1818181818181818, 'number': 119} | {'precision': 0.4142857142857143, 'recall': 0.5446009389671361, 'f1': 0.4705882352941177, 'number': 1065} | 0.3441 | 0.4982 | 0.4071 | 0.5598 |
62
+ | 1.0207 | 5.0 | 50 | 1.1986 | {'precision': 0.3122302158273381, 'recall': 0.5364647713226205, 'f1': 0.39472487494315595, 'number': 809} | {'precision': 0.2696629213483146, 'recall': 0.20168067226890757, 'f1': 0.23076923076923078, 'number': 119} | {'precision': 0.43670411985018726, 'recall': 0.5474178403755868, 'f1': 0.48583333333333334, 'number': 1065} | 0.3699 | 0.5223 | 0.4331 | 0.5405 |
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+ | 0.9534 | 6.0 | 60 | 1.1446 | {'precision': 0.32223796033994334, 'recall': 0.5624227441285538, 'f1': 0.4097253489419181, 'number': 809} | {'precision': 0.3, 'recall': 0.17647058823529413, 'f1': 0.22222222222222224, 'number': 119} | {'precision': 0.48997995991983967, 'recall': 0.4591549295774648, 'f1': 0.47406689287445475, 'number': 1065} | 0.3891 | 0.4842 | 0.4315 | 0.5634 |
64
+ | 0.854 | 7.0 | 70 | 1.0533 | {'precision': 0.38318777292576417, 'recall': 0.4338689740420272, 'f1': 0.4069565217391304, 'number': 809} | {'precision': 0.264, 'recall': 0.2773109243697479, 'f1': 0.27049180327868855, 'number': 119} | {'precision': 0.4503968253968254, 'recall': 0.6394366197183099, 'f1': 0.5285215366705472, 'number': 1065} | 0.4172 | 0.5344 | 0.4685 | 0.5950 |
65
+ | 0.7821 | 8.0 | 80 | 1.0447 | {'precision': 0.3707482993197279, 'recall': 0.5389369592088998, 'f1': 0.43929471032745593, 'number': 809} | {'precision': 0.3373493975903614, 'recall': 0.23529411764705882, 'f1': 0.2772277227722772, 'number': 119} | {'precision': 0.4789594491201224, 'recall': 0.5877934272300469, 'f1': 0.5278246205733558, 'number': 1065} | 0.4248 | 0.5469 | 0.4782 | 0.6234 |
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+ | 0.7222 | 10.0 | 100 | 1.0862 | {'precision': 0.36459246275197194, 'recall': 0.5142150803461063, 'f1': 0.42666666666666664, 'number': 809} | {'precision': 0.33, 'recall': 0.2773109243697479, 'f1': 0.30136986301369867, 'number': 119} | {'precision': 0.48, 'recall': 0.6422535211267606, 'f1': 0.5493975903614458, 'number': 1065} | 0.4250 | 0.5685 | 0.4864 | 0.6184 |
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+ | 0.3301 | 20.0 | 200 | 1.3047 | {'precision': 0.4407239819004525, 'recall': 0.6019777503090235, 'f1': 0.5088819226750262, 'number': 809} | {'precision': 0.3695652173913043, 'recall': 0.2857142857142857, 'f1': 0.3222748815165877, 'number': 119} | {'precision': 0.595724907063197, 'recall': 0.6018779342723005, 'f1': 0.5987856141989725, 'number': 1065} | 0.5112 | 0.5830 | 0.5448 | 0.6240 |
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+ | 0.254 | 24.0 | 240 | 1.3707 | {'precision': 0.4535353535353535, 'recall': 0.5550061804697157, 'f1': 0.4991662034463591, 'number': 809} | {'precision': 0.32432432432432434, 'recall': 0.3025210084033613, 'f1': 0.31304347826086953, 'number': 119} | {'precision': 0.5873949579831933, 'recall': 0.6563380281690141, 'f1': 0.6199556541019955, 'number': 1065} | 0.5168 | 0.5941 | 0.5528 | 0.6305 |
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+ | 0.2268 | 26.0 | 260 | 1.4138 | {'precision': 0.4505386875612145, 'recall': 0.5686032138442522, 'f1': 0.5027322404371585, 'number': 809} | {'precision': 0.36363636363636365, 'recall': 0.2689075630252101, 'f1': 0.30917874396135264, 'number': 119} | {'precision': 0.5654281098546042, 'recall': 0.6572769953051644, 'f1': 0.60790273556231, 'number': 1065} | 0.5079 | 0.5981 | 0.5493 | 0.6302 |
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+ | 0.2078 | 28.0 | 280 | 1.4767 | {'precision': 0.49171270718232046, 'recall': 0.5500618046971569, 'f1': 0.5192532088681446, 'number': 809} | {'precision': 0.3389830508474576, 'recall': 0.33613445378151263, 'f1': 0.3375527426160338, 'number': 119} | {'precision': 0.5939849624060151, 'recall': 0.6676056338028169, 'f1': 0.6286472148541113, 'number': 1065} | 0.5387 | 0.6001 | 0.5678 | 0.6361 |
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+ | 0.196 | 29.0 | 290 | 1.4066 | {'precision': 0.46553446553446554, 'recall': 0.5760197775030902, 'f1': 0.5149171270718232, 'number': 809} | {'precision': 0.375, 'recall': 0.2773109243697479, 'f1': 0.31884057971014496, 'number': 119} | {'precision': 0.5620031796502385, 'recall': 0.6638497652582159, 'f1': 0.6086956521739131, 'number': 1065} | 0.5138 | 0.6051 | 0.5558 | 0.6452 |
87
+ | 0.1834 | 30.0 | 300 | 1.5397 | {'precision': 0.4612286002014099, 'recall': 0.5661310259579728, 'f1': 0.5083240843507214, 'number': 809} | {'precision': 0.3235294117647059, 'recall': 0.2773109243697479, 'f1': 0.2986425339366516, 'number': 119} | {'precision': 0.5724815724815725, 'recall': 0.6563380281690141, 'f1': 0.6115485564304461, 'number': 1065} | 0.5138 | 0.5971 | 0.5523 | 0.6241 |
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+ | 0.1701 | 31.0 | 310 | 1.5250 | {'precision': 0.4490566037735849, 'recall': 0.588380716934487, 'f1': 0.50936329588015, 'number': 809} | {'precision': 0.3764705882352941, 'recall': 0.2689075630252101, 'f1': 0.3137254901960785, 'number': 119} | {'precision': 0.5677685950413223, 'recall': 0.6450704225352113, 'f1': 0.6039560439560439, 'number': 1065} | 0.5074 | 0.5996 | 0.5497 | 0.6348 |
89
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90
+ | 0.1576 | 33.0 | 330 | 1.5256 | {'precision': 0.47274529236868185, 'recall': 0.5896168108776267, 'f1': 0.5247524752475247, 'number': 809} | {'precision': 0.36538461538461536, 'recall': 0.31932773109243695, 'f1': 0.34080717488789236, 'number': 119} | {'precision': 0.5860621326616289, 'recall': 0.6553990610328638, 'f1': 0.6187943262411348, 'number': 1065} | 0.5265 | 0.6086 | 0.5646 | 0.6393 |
91
+ | 0.1444 | 34.0 | 340 | 1.5900 | {'precision': 0.4597478176527643, 'recall': 0.5859085290482077, 'f1': 0.5152173913043477, 'number': 809} | {'precision': 0.3870967741935484, 'recall': 0.3025210084033613, 'f1': 0.339622641509434, 'number': 119} | {'precision': 0.5847953216374269, 'recall': 0.6572769953051644, 'f1': 0.6189213085764811, 'number': 1065} | 0.5213 | 0.6071 | 0.5610 | 0.6348 |
92
+ | 0.1447 | 35.0 | 350 | 1.6271 | {'precision': 0.4558011049723757, 'recall': 0.6118665018541409, 'f1': 0.5224274406332453, 'number': 809} | {'precision': 0.46153846153846156, 'recall': 0.3025210084033613, 'f1': 0.3654822335025381, 'number': 119} | {'precision': 0.6021602160216022, 'recall': 0.6281690140845071, 'f1': 0.614889705882353, 'number': 1065} | 0.5275 | 0.6021 | 0.5623 | 0.6400 |
93
+ | 0.1403 | 36.0 | 360 | 1.6242 | {'precision': 0.4578313253012048, 'recall': 0.6106304079110012, 'f1': 0.5233050847457628, 'number': 809} | {'precision': 0.4177215189873418, 'recall': 0.2773109243697479, 'f1': 0.33333333333333337, 'number': 119} | {'precision': 0.603060306030603, 'recall': 0.6291079812206573, 'f1': 0.6158088235294117, 'number': 1065} | 0.5275 | 0.6006 | 0.5617 | 0.6299 |
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+ | 0.1302 | 37.0 | 370 | 1.5982 | {'precision': 0.4633458646616541, 'recall': 0.6093943139678616, 'f1': 0.5264281900694073, 'number': 809} | {'precision': 0.3162393162393162, 'recall': 0.31092436974789917, 'f1': 0.3135593220338983, 'number': 119} | {'precision': 0.5850877192982457, 'recall': 0.6262910798122066, 'f1': 0.6049886621315193, 'number': 1065} | 0.5157 | 0.6006 | 0.5549 | 0.6334 |
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+ | 0.1224 | 39.0 | 390 | 1.6212 | {'precision': 0.46387832699619774, 'recall': 0.6032138442521632, 'f1': 0.5244492208490059, 'number': 809} | {'precision': 0.3977272727272727, 'recall': 0.29411764705882354, 'f1': 0.3381642512077294, 'number': 119} | {'precision': 0.5654320987654321, 'recall': 0.6450704225352113, 'f1': 0.6026315789473683, 'number': 1065} | 0.5138 | 0.6071 | 0.5566 | 0.6420 |
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100
+ | 0.1052 | 43.0 | 430 | 1.6521 | {'precision': 0.4725609756097561, 'recall': 0.5747836835599506, 'f1': 0.5186837702175126, 'number': 809} | {'precision': 0.4166666666666667, 'recall': 0.33613445378151263, 'f1': 0.37209302325581406, 'number': 119} | {'precision': 0.5882838283828383, 'recall': 0.6694835680751173, 'f1': 0.6262626262626263, 'number': 1065} | 0.5314 | 0.6111 | 0.5685 | 0.6406 |
101
+ | 0.1024 | 44.0 | 440 | 1.6361 | {'precision': 0.47112462006079026, 'recall': 0.5747836835599506, 'f1': 0.5178173719376392, 'number': 809} | {'precision': 0.43010752688172044, 'recall': 0.33613445378151263, 'f1': 0.37735849056603776, 'number': 119} | {'precision': 0.5836038961038961, 'recall': 0.6751173708920187, 'f1': 0.6260339573356551, 'number': 1065} | 0.5294 | 0.6141 | 0.5686 | 0.6430 |
102
+ | 0.099 | 45.0 | 450 | 1.6565 | {'precision': 0.4645222327341533, 'recall': 0.6069221260815822, 'f1': 0.5262593783494106, 'number': 809} | {'precision': 0.43956043956043955, 'recall': 0.33613445378151263, 'f1': 0.380952380952381, 'number': 119} | {'precision': 0.5934819897084048, 'recall': 0.6497652582159624, 'f1': 0.6203496190049306, 'number': 1065} | 0.5285 | 0.6136 | 0.5679 | 0.6429 |
103
+ | 0.0993 | 46.0 | 460 | 1.6493 | {'precision': 0.46771037181996084, 'recall': 0.5908529048207664, 'f1': 0.5221190606226106, 'number': 809} | {'precision': 0.43023255813953487, 'recall': 0.31092436974789917, 'f1': 0.36097560975609755, 'number': 119} | {'precision': 0.5841004184100418, 'recall': 0.6553990610328638, 'f1': 0.6176991150442477, 'number': 1065} | 0.5267 | 0.6086 | 0.5647 | 0.6373 |
104
+ | 0.0997 | 47.0 | 470 | 1.6391 | {'precision': 0.46400778210116733, 'recall': 0.5896168108776267, 'f1': 0.5193249863908546, 'number': 809} | {'precision': 0.41304347826086957, 'recall': 0.31932773109243695, 'f1': 0.3601895734597156, 'number': 119} | {'precision': 0.5760065735414954, 'recall': 0.6582159624413145, 'f1': 0.614373356704645, 'number': 1065} | 0.5203 | 0.6101 | 0.5617 | 0.6411 |
105
+ | 0.0951 | 48.0 | 480 | 1.6616 | {'precision': 0.4644308943089431, 'recall': 0.5648949320148331, 'f1': 0.5097601784718349, 'number': 809} | {'precision': 0.43157894736842106, 'recall': 0.3445378151260504, 'f1': 0.38317757009345793, 'number': 119} | {'precision': 0.5755336617405583, 'recall': 0.6582159624413145, 'f1': 0.6141042487954446, 'number': 1065} | 0.5220 | 0.6016 | 0.5590 | 0.6357 |
106
+ | 0.0957 | 49.0 | 490 | 1.6806 | {'precision': 0.46360917248255235, 'recall': 0.5747836835599506, 'f1': 0.5132450331125828, 'number': 809} | {'precision': 0.4418604651162791, 'recall': 0.31932773109243695, 'f1': 0.3707317073170731, 'number': 119} | {'precision': 0.5841666666666666, 'recall': 0.6582159624413145, 'f1': 0.6189845474613687, 'number': 1065} | 0.5260 | 0.6041 | 0.5624 | 0.6392 |
107
+ | 0.0896 | 50.0 | 500 | 1.6784 | {'precision': 0.4630541871921182, 'recall': 0.580964153275649, 'f1': 0.5153508771929824, 'number': 809} | {'precision': 0.4470588235294118, 'recall': 0.31932773109243695, 'f1': 0.37254901960784315, 'number': 119} | {'precision': 0.5822259136212624, 'recall': 0.6582159624413145, 'f1': 0.617893345085941, 'number': 1065} | 0.5247 | 0.6066 | 0.5627 | 0.6411 |
108
 
109
 
110
  ### Framework versions
logs/events.out.tfevents.1710848341.debb6005789e.10976.0 CHANGED
@@ -1,3 +1,3 @@
1
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