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layoutlm-custom_no_text

Token Classification
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Safetensors
layoutlm
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End of training

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  1. README.md +60 -25
  2. logs/events.out.tfevents.1704880032.46361b17fc6b.3222.0 +2 -2
  3. model.safetensors +1 -1
README.md CHANGED
@@ -15,13 +15,13 @@ 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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3594
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- - Noise: {'precision': 0.5976627712854758, 'recall': 0.5700636942675159, 'f1': 0.5835370823145885, 'number': 628}
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- - Signal: {'precision': 0.5559265442404007, 'recall': 0.5302547770700637, 'f1': 0.5427872860635697, 'number': 628}
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- - Overall Precision: 0.5768
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- - Overall Recall: 0.5502
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- - Overall F1: 0.5632
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- - Overall Accuracy: 0.8777
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  ## Model description
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@@ -46,28 +46,63 @@ 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: 15
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  - mixed_precision_training: Native AMP
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52
  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Noise | Signal | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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- | 0.5172 | 1.0 | 18 | 0.4915 | {'precision': 0.3973288814691152, 'recall': 0.37898089171974525, 'f1': 0.3879380603096985, 'number': 628} | {'precision': 0.36894824707846413, 'recall': 0.3519108280254777, 'f1': 0.3602281988590057, 'number': 628} | 0.3831 | 0.3654 | 0.3741 | 0.7779 |
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- | 0.4057 | 2.0 | 36 | 0.4306 | {'precision': 0.42788461538461536, 'recall': 0.4251592356687898, 'f1': 0.426517571884984, 'number': 628} | {'precision': 0.3766025641025641, 'recall': 0.37420382165605093, 'f1': 0.3753993610223642, 'number': 628} | 0.4022 | 0.3997 | 0.4010 | 0.8151 |
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- | 0.3616 | 3.0 | 54 | 0.4145 | {'precision': 0.444633730834753, 'recall': 0.4156050955414013, 'f1': 0.4296296296296297, 'number': 628} | {'precision': 0.41056218057921634, 'recall': 0.3837579617834395, 'f1': 0.3967078189300412, 'number': 628} | 0.4276 | 0.3997 | 0.4132 | 0.8237 |
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- | 0.3278 | 4.0 | 72 | 0.3994 | {'precision': 0.5050167224080268, 'recall': 0.48089171974522293, 'f1': 0.4926590538336052, 'number': 628} | {'precision': 0.4698996655518395, 'recall': 0.44745222929936307, 'f1': 0.4584013050570963, 'number': 628} | 0.4875 | 0.4642 | 0.4755 | 0.8366 |
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- | 0.2966 | 5.0 | 90 | 0.3795 | {'precision': 0.5129533678756477, 'recall': 0.4729299363057325, 'f1': 0.49212924606462305, 'number': 628} | {'precision': 0.5043177892918825, 'recall': 0.46496815286624205, 'f1': 0.48384424192212094, 'number': 628} | 0.5086 | 0.4689 | 0.4880 | 0.8489 |
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- | 0.2717 | 6.0 | 108 | 0.3526 | {'precision': 0.5459272097053726, 'recall': 0.5015923566878981, 'f1': 0.5228215767634854, 'number': 628} | {'precision': 0.511265164644714, 'recall': 0.4697452229299363, 'f1': 0.48962655601659755, 'number': 628} | 0.5286 | 0.4857 | 0.5062 | 0.8581 |
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- | 0.2441 | 7.0 | 126 | 0.3400 | {'precision': 0.5338208409506399, 'recall': 0.46496815286624205, 'f1': 0.4970212765957447, 'number': 628} | {'precision': 0.49725776965265084, 'recall': 0.43312101910828027, 'f1': 0.4629787234042553, 'number': 628} | 0.5155 | 0.4490 | 0.4800 | 0.8598 |
63
- | 0.224 | 8.0 | 144 | 0.3324 | {'precision': 0.563922942206655, 'recall': 0.5127388535031847, 'f1': 0.5371142618849041, 'number': 628} | {'precision': 0.5288966725043783, 'recall': 0.48089171974522293, 'f1': 0.5037531276063387, 'number': 628} | 0.5464 | 0.4968 | 0.5204 | 0.8673 |
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- | 0.2044 | 9.0 | 162 | 0.3249 | {'precision': 0.5833333333333334, 'recall': 0.535031847133758, 'f1': 0.558139534883721, 'number': 628} | {'precision': 0.5347222222222222, 'recall': 0.49044585987261147, 'f1': 0.5116279069767441, 'number': 628} | 0.5590 | 0.5127 | 0.5349 | 0.8726 |
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- | 0.1914 | 10.0 | 180 | 0.3481 | {'precision': 0.5597920277296361, 'recall': 0.5143312101910829, 'f1': 0.5360995850622408, 'number': 628} | {'precision': 0.511265164644714, 'recall': 0.4697452229299363, 'f1': 0.48962655601659755, 'number': 628} | 0.5355 | 0.4920 | 0.5129 | 0.8645 |
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- | 0.1823 | 11.0 | 198 | 0.3412 | {'precision': 0.5963756177924218, 'recall': 0.5764331210191083, 'f1': 0.5862348178137652, 'number': 628} | {'precision': 0.5667215815485996, 'recall': 0.5477707006369427, 'f1': 0.557085020242915, 'number': 628} | 0.5815 | 0.5621 | 0.5717 | 0.8810 |
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- | 0.1672 | 12.0 | 216 | 0.3496 | {'precision': 0.5791245791245792, 'recall': 0.5477707006369427, 'f1': 0.563011456628478, 'number': 628} | {'precision': 0.5420875420875421, 'recall': 0.5127388535031847, 'f1': 0.5270049099836335, 'number': 628} | 0.5606 | 0.5303 | 0.5450 | 0.8735 |
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- | 0.1627 | 13.0 | 234 | 0.3675 | {'precision': 0.5953565505804311, 'recall': 0.571656050955414, 'f1': 0.5832656376929325, 'number': 628} | {'precision': 0.5621890547263682, 'recall': 0.5398089171974523, 'f1': 0.5507717303005686, 'number': 628} | 0.5788 | 0.5557 | 0.5670 | 0.8779 |
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- | 0.1592 | 14.0 | 252 | 0.3562 | {'precision': 0.596694214876033, 'recall': 0.5748407643312102, 'f1': 0.5855636658556367, 'number': 628} | {'precision': 0.5504132231404959, 'recall': 0.5302547770700637, 'f1': 0.5401459854014599, 'number': 628} | 0.5736 | 0.5525 | 0.5629 | 0.8757 |
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- | 0.1553 | 15.0 | 270 | 0.3594 | {'precision': 0.5976627712854758, 'recall': 0.5700636942675159, 'f1': 0.5835370823145885, 'number': 628} | {'precision': 0.5559265442404007, 'recall': 0.5302547770700637, 'f1': 0.5427872860635697, 'number': 628} | 0.5768 | 0.5502 | 0.5632 | 0.8777 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
 
15
 
16
  This model is a fine-tuned version of [microsoft/layoutlm-base-uncased](https://huggingface.co/microsoft/layoutlm-base-uncased) on the None dataset.
17
  It achieves the following results on the evaluation set:
18
+ - Loss: 0.5142
19
+ - Noise: {'precision': 0.6764705882352942, 'recall': 0.6695205479452054, 'f1': 0.6729776247848538, 'number': 584}
20
+ - Signal: {'precision': 0.629757785467128, 'recall': 0.6232876712328768, 'f1': 0.6265060240963856, 'number': 584}
21
+ - Overall Precision: 0.6531
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+ - Overall Recall: 0.6464
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+ - Overall F1: 0.6497
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+ - Overall Accuracy: 0.9156
25
 
26
  ## Model description
27
 
 
46
  - seed: 42
47
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
48
  - lr_scheduler_type: linear
49
+ - num_epochs: 50
50
  - mixed_precision_training: Native AMP
51
 
52
  ### Training results
53
 
54
+ | Training Loss | Epoch | Step | Validation Loss | Noise | Signal | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
55
+ |:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 0.5712 | 1.0 | 18 | 0.4356 | {'precision': 0.3712374581939799, 'recall': 0.3801369863013699, 'f1': 0.3756345177664975, 'number': 584} | {'precision': 0.3294314381270903, 'recall': 0.3373287671232877, 'f1': 0.3333333333333333, 'number': 584} | 0.3503 | 0.3587 | 0.3545 | 0.8008 |
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+ | 0.4233 | 2.0 | 36 | 0.3745 | {'precision': 0.4048964218455744, 'recall': 0.3681506849315068, 'f1': 0.38565022421524664, 'number': 584} | {'precision': 0.3483992467043315, 'recall': 0.3167808219178082, 'f1': 0.33183856502242154, 'number': 584} | 0.3766 | 0.3425 | 0.3587 | 0.8287 |
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+ | 0.3817 | 3.0 | 54 | 0.3632 | {'precision': 0.45740740740740743, 'recall': 0.4229452054794521, 'f1': 0.43950177935943063, 'number': 584} | {'precision': 0.3851851851851852, 'recall': 0.3561643835616438, 'f1': 0.3701067615658363, 'number': 584} | 0.4213 | 0.3896 | 0.4048 | 0.8413 |
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+ | 0.3472 | 4.0 | 72 | 0.3133 | {'precision': 0.5143953934740882, 'recall': 0.4589041095890411, 'f1': 0.4850678733031674, 'number': 584} | {'precision': 0.43378119001919385, 'recall': 0.386986301369863, 'f1': 0.40904977375565615, 'number': 584} | 0.4741 | 0.4229 | 0.4471 | 0.8550 |
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+ | 0.3132 | 5.0 | 90 | 0.3254 | {'precision': 0.5112016293279023, 'recall': 0.4297945205479452, 'f1': 0.4669767441860465, 'number': 584} | {'precision': 0.4460285132382892, 'recall': 0.375, 'f1': 0.4074418604651162, 'number': 584} | 0.4786 | 0.4024 | 0.4372 | 0.8525 |
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+ | 0.282 | 6.0 | 108 | 0.3033 | {'precision': 0.5387453874538746, 'recall': 0.5, 'f1': 0.5186500888099467, 'number': 584} | {'precision': 0.46863468634686345, 'recall': 0.4349315068493151, 'f1': 0.45115452930728245, 'number': 584} | 0.5037 | 0.4675 | 0.4849 | 0.8656 |
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+ | 0.2486 | 7.0 | 126 | 0.2827 | {'precision': 0.5498220640569395, 'recall': 0.5291095890410958, 'f1': 0.5392670157068062, 'number': 584} | {'precision': 0.5071174377224199, 'recall': 0.488013698630137, 'f1': 0.49738219895287955, 'number': 584} | 0.5285 | 0.5086 | 0.5183 | 0.8773 |
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+ | 0.2276 | 8.0 | 144 | 0.2798 | {'precision': 0.5597826086956522, 'recall': 0.5291095890410958, 'f1': 0.5440140845070423, 'number': 584} | {'precision': 0.5235507246376812, 'recall': 0.4948630136986301, 'f1': 0.5088028169014084, 'number': 584} | 0.5417 | 0.5120 | 0.5264 | 0.8793 |
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+ | 0.197 | 9.0 | 162 | 0.2778 | {'precision': 0.5948905109489051, 'recall': 0.5582191780821918, 'f1': 0.5759717314487632, 'number': 584} | {'precision': 0.5602189781021898, 'recall': 0.5256849315068494, 'f1': 0.5424028268551236, 'number': 584} | 0.5776 | 0.5420 | 0.5592 | 0.8891 |
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+ | 0.1812 | 10.0 | 180 | 0.2932 | {'precision': 0.5907407407407408, 'recall': 0.5462328767123288, 'f1': 0.5676156583629893, 'number': 584} | {'precision': 0.5666666666666667, 'recall': 0.523972602739726, 'f1': 0.5444839857651246, 'number': 584} | 0.5787 | 0.5351 | 0.5560 | 0.8888 |
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+ | 0.1611 | 11.0 | 198 | 0.2785 | {'precision': 0.6156648451730419, 'recall': 0.5787671232876712, 'f1': 0.5966460723742276, 'number': 584} | {'precision': 0.5719489981785064, 'recall': 0.5376712328767124, 'f1': 0.5542806707855252, 'number': 584} | 0.5938 | 0.5582 | 0.5755 | 0.8991 |
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+ | 0.1441 | 12.0 | 216 | 0.2738 | {'precision': 0.6263537906137184, 'recall': 0.5941780821917808, 'f1': 0.6098418277680141, 'number': 584} | {'precision': 0.5776173285198556, 'recall': 0.547945205479452, 'f1': 0.562390158172232, 'number': 584} | 0.6020 | 0.5711 | 0.5861 | 0.9016 |
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+ | 0.1294 | 13.0 | 234 | 0.3072 | {'precision': 0.6201413427561837, 'recall': 0.601027397260274, 'f1': 0.6104347826086957, 'number': 584} | {'precision': 0.5795053003533569, 'recall': 0.5616438356164384, 'f1': 0.5704347826086956, 'number': 584} | 0.5998 | 0.5813 | 0.5904 | 0.8989 |
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+ | 0.1218 | 14.0 | 252 | 0.2963 | {'precision': 0.629695885509839, 'recall': 0.6027397260273972, 'f1': 0.6159230096237971, 'number': 584} | {'precision': 0.5849731663685152, 'recall': 0.559931506849315, 'f1': 0.5721784776902886, 'number': 584} | 0.6073 | 0.5813 | 0.5941 | 0.9030 |
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+ | 0.1032 | 15.0 | 270 | 0.3365 | {'precision': 0.6106194690265486, 'recall': 0.5907534246575342, 'f1': 0.6005221932114881, 'number': 584} | {'precision': 0.5681415929203539, 'recall': 0.5496575342465754, 'f1': 0.5587467362924282, 'number': 584} | 0.5894 | 0.5702 | 0.5796 | 0.8991 |
71
+ | 0.0981 | 16.0 | 288 | 0.3342 | {'precision': 0.631858407079646, 'recall': 0.6113013698630136, 'f1': 0.6214099216710183, 'number': 584} | {'precision': 0.5893805309734513, 'recall': 0.5702054794520548, 'f1': 0.5796344647519582, 'number': 584} | 0.6106 | 0.5908 | 0.6005 | 0.9039 |
72
+ | 0.0844 | 17.0 | 306 | 0.3543 | {'precision': 0.6502636203866432, 'recall': 0.6335616438356164, 'f1': 0.6418039895923676, 'number': 584} | {'precision': 0.5957820738137083, 'recall': 0.5804794520547946, 'f1': 0.5880312228967911, 'number': 584} | 0.6230 | 0.6070 | 0.6149 | 0.9050 |
73
+ | 0.0763 | 18.0 | 324 | 0.3559 | {'precision': 0.6392294220665499, 'recall': 0.625, 'f1': 0.632034632034632, 'number': 584} | {'precision': 0.5989492119089317, 'recall': 0.5856164383561644, 'f1': 0.5922077922077922, 'number': 584} | 0.6191 | 0.6053 | 0.6121 | 0.9075 |
74
+ | 0.0682 | 19.0 | 342 | 0.3599 | {'precision': 0.6666666666666666, 'recall': 0.6335616438356164, 'f1': 0.6496927129060578, 'number': 584} | {'precision': 0.618018018018018, 'recall': 0.5873287671232876, 'f1': 0.6022827041264267, 'number': 584} | 0.6423 | 0.6104 | 0.6260 | 0.9086 |
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+ | 0.0685 | 20.0 | 360 | 0.3574 | {'precision': 0.670863309352518, 'recall': 0.6386986301369864, 'f1': 0.6543859649122807, 'number': 584} | {'precision': 0.6151079136690647, 'recall': 0.5856164383561644, 'f1': 0.6, 'number': 584} | 0.6430 | 0.6122 | 0.6272 | 0.9114 |
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+ | 0.0591 | 21.0 | 378 | 0.3742 | {'precision': 0.6573426573426573, 'recall': 0.6438356164383562, 'f1': 0.6505190311418684, 'number': 584} | {'precision': 0.6171328671328671, 'recall': 0.6044520547945206, 'f1': 0.6107266435986158, 'number': 584} | 0.6372 | 0.6241 | 0.6306 | 0.9100 |
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+ | 0.0521 | 22.0 | 396 | 0.4063 | {'precision': 0.6566901408450704, 'recall': 0.6386986301369864, 'f1': 0.6475694444444444, 'number': 584} | {'precision': 0.6161971830985915, 'recall': 0.5993150684931506, 'f1': 0.607638888888889, 'number': 584} | 0.6364 | 0.6190 | 0.6276 | 0.9095 |
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+ | 0.0492 | 23.0 | 414 | 0.3971 | {'precision': 0.649737302977233, 'recall': 0.6352739726027398, 'f1': 0.6424242424242426, 'number': 584} | {'precision': 0.5971978984238179, 'recall': 0.583904109589041, 'f1': 0.5904761904761905, 'number': 584} | 0.6235 | 0.6096 | 0.6165 | 0.9086 |
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+ | 0.045 | 24.0 | 432 | 0.4198 | {'precision': 0.6448275862068965, 'recall': 0.6404109589041096, 'f1': 0.6426116838487972, 'number': 584} | {'precision': 0.5948275862068966, 'recall': 0.5907534246575342, 'f1': 0.5927835051546393, 'number': 584} | 0.6198 | 0.6156 | 0.6177 | 0.9061 |
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+ | 0.0391 | 25.0 | 450 | 0.4477 | {'precision': 0.643979057591623, 'recall': 0.6318493150684932, 'f1': 0.6378565254969749, 'number': 584} | {'precision': 0.5986038394415357, 'recall': 0.5873287671232876, 'f1': 0.5929127052722557, 'number': 584} | 0.6213 | 0.6096 | 0.6154 | 0.9061 |
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+ | 0.0411 | 26.0 | 468 | 0.4080 | {'precision': 0.6400679117147708, 'recall': 0.6455479452054794, 'f1': 0.6427962489343563, 'number': 584} | {'precision': 0.597623089983022, 'recall': 0.6027397260273972, 'f1': 0.6001705029838021, 'number': 584} | 0.6188 | 0.6241 | 0.6215 | 0.9084 |
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+ | 0.0369 | 27.0 | 486 | 0.4339 | {'precision': 0.6614035087719298, 'recall': 0.6455479452054794, 'f1': 0.6533795493934141, 'number': 584} | {'precision': 0.6105263157894737, 'recall': 0.5958904109589042, 'f1': 0.6031195840554593, 'number': 584} | 0.6360 | 0.6207 | 0.6282 | 0.9103 |
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+ | 0.0315 | 28.0 | 504 | 0.4303 | {'precision': 0.6637931034482759, 'recall': 0.6592465753424658, 'f1': 0.6615120274914089, 'number': 584} | {'precision': 0.6137931034482759, 'recall': 0.6095890410958904, 'f1': 0.6116838487972508, 'number': 584} | 0.6388 | 0.6344 | 0.6366 | 0.9117 |
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+ | 0.0332 | 29.0 | 522 | 0.4253 | {'precision': 0.6643717728055077, 'recall': 0.660958904109589, 'f1': 0.6626609442060085, 'number': 584} | {'precision': 0.6179001721170396, 'recall': 0.6147260273972602, 'f1': 0.6163090128755364, 'number': 584} | 0.6411 | 0.6378 | 0.6395 | 0.9134 |
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+ | 0.0272 | 30.0 | 540 | 0.4594 | {'precision': 0.6495726495726496, 'recall': 0.6506849315068494, 'f1': 0.6501283147989735, 'number': 584} | {'precision': 0.5931623931623932, 'recall': 0.5941780821917808, 'f1': 0.5936698032506416, 'number': 584} | 0.6214 | 0.6224 | 0.6219 | 0.9078 |
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+ | 0.027 | 31.0 | 558 | 0.4680 | {'precision': 0.6621160409556314, 'recall': 0.6643835616438356, 'f1': 0.6632478632478632, 'number': 584} | {'precision': 0.6143344709897611, 'recall': 0.6164383561643836, 'f1': 0.6153846153846154, 'number': 584} | 0.6382 | 0.6404 | 0.6393 | 0.9111 |
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+ | 0.0295 | 32.0 | 576 | 0.4367 | {'precision': 0.6719022687609075, 'recall': 0.6592465753424658, 'f1': 0.6655142610198791, 'number': 584} | {'precision': 0.612565445026178, 'recall': 0.601027397260274, 'f1': 0.6067415730337079, 'number': 584} | 0.6422 | 0.6301 | 0.6361 | 0.9120 |
88
+ | 0.0216 | 33.0 | 594 | 0.4674 | {'precision': 0.681260945709282, 'recall': 0.666095890410959, 'f1': 0.6735930735930735, 'number': 584} | {'precision': 0.6357267950963222, 'recall': 0.6215753424657534, 'f1': 0.6285714285714286, 'number': 584} | 0.6585 | 0.6438 | 0.6511 | 0.9139 |
89
+ | 0.0212 | 34.0 | 612 | 0.4702 | {'precision': 0.6666666666666666, 'recall': 0.6643835616438356, 'f1': 0.6655231560891938, 'number': 584} | {'precision': 0.6202749140893471, 'recall': 0.6181506849315068, 'f1': 0.6192109777015438, 'number': 584} | 0.6435 | 0.6413 | 0.6424 | 0.9103 |
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+ | 0.0227 | 35.0 | 630 | 0.4637 | {'precision': 0.657672849915683, 'recall': 0.6678082191780822, 'f1': 0.6627017841971112, 'number': 584} | {'precision': 0.6155143338954469, 'recall': 0.625, 'f1': 0.6202209005947323, 'number': 584} | 0.6366 | 0.6464 | 0.6415 | 0.9109 |
91
+ | 0.0196 | 36.0 | 648 | 0.4639 | {'precision': 0.6660899653979239, 'recall': 0.6592465753424658, 'f1': 0.6626506024096386, 'number': 584} | {'precision': 0.6141868512110726, 'recall': 0.6078767123287672, 'f1': 0.6110154905335629, 'number': 584} | 0.6401 | 0.6336 | 0.6368 | 0.9125 |
92
+ | 0.0183 | 37.0 | 666 | 0.4656 | {'precision': 0.6632478632478632, 'recall': 0.6643835616438356, 'f1': 0.6638152266894781, 'number': 584} | {'precision': 0.6, 'recall': 0.601027397260274, 'f1': 0.6005132591958939, 'number': 584} | 0.6316 | 0.6327 | 0.6322 | 0.9131 |
93
+ | 0.0209 | 38.0 | 684 | 0.4754 | {'precision': 0.6649214659685864, 'recall': 0.6523972602739726, 'f1': 0.658599827139153, 'number': 584} | {'precision': 0.6073298429319371, 'recall': 0.5958904109589042, 'f1': 0.6015557476231633, 'number': 584} | 0.6361 | 0.6241 | 0.6301 | 0.9131 |
94
+ | 0.0166 | 39.0 | 702 | 0.4703 | {'precision': 0.6695352839931153, 'recall': 0.666095890410959, 'f1': 0.6678111587982833, 'number': 584} | {'precision': 0.612736660929432, 'recall': 0.6095890410958904, 'f1': 0.6111587982832618, 'number': 584} | 0.6411 | 0.6378 | 0.6395 | 0.9151 |
95
+ | 0.0152 | 40.0 | 720 | 0.4739 | {'precision': 0.6626712328767124, 'recall': 0.6626712328767124, 'f1': 0.6626712328767124, 'number': 584} | {'precision': 0.6215753424657534, 'recall': 0.6215753424657534, 'f1': 0.6215753424657534, 'number': 584} | 0.6421 | 0.6421 | 0.6421 | 0.9139 |
96
+ | 0.0173 | 41.0 | 738 | 0.4839 | {'precision': 0.6610738255033557, 'recall': 0.6746575342465754, 'f1': 0.6677966101694915, 'number': 584} | {'precision': 0.6191275167785235, 'recall': 0.6318493150684932, 'f1': 0.6254237288135593, 'number': 584} | 0.6401 | 0.6533 | 0.6466 | 0.9139 |
97
+ | 0.0162 | 42.0 | 756 | 0.4854 | {'precision': 0.6610455311973018, 'recall': 0.6712328767123288, 'f1': 0.6661002548853017, 'number': 584} | {'precision': 0.6138279932546374, 'recall': 0.6232876712328768, 'f1': 0.6185216652506373, 'number': 584} | 0.6374 | 0.6473 | 0.6423 | 0.9156 |
98
+ | 0.0186 | 43.0 | 774 | 0.4747 | {'precision': 0.666095890410959, 'recall': 0.666095890410959, 'f1': 0.666095890410959, 'number': 584} | {'precision': 0.6061643835616438, 'recall': 0.6061643835616438, 'f1': 0.6061643835616438, 'number': 584} | 0.6361 | 0.6361 | 0.6361 | 0.9156 |
99
+ | 0.0149 | 44.0 | 792 | 0.4920 | {'precision': 0.6695501730103807, 'recall': 0.6626712328767124, 'f1': 0.666092943201377, 'number': 584} | {'precision': 0.6141868512110726, 'recall': 0.6078767123287672, 'f1': 0.6110154905335629, 'number': 584} | 0.6419 | 0.6353 | 0.6386 | 0.9139 |
100
+ | 0.0126 | 45.0 | 810 | 0.4911 | {'precision': 0.6621392190152802, 'recall': 0.6678082191780822, 'f1': 0.6649616368286446, 'number': 584} | {'precision': 0.6146010186757216, 'recall': 0.6198630136986302, 'f1': 0.6172208013640239, 'number': 584} | 0.6384 | 0.6438 | 0.6411 | 0.9117 |
101
+ | 0.0142 | 46.0 | 828 | 0.4932 | {'precision': 0.671280276816609, 'recall': 0.6643835616438356, 'f1': 0.6678141135972462, 'number': 584} | {'precision': 0.6228373702422145, 'recall': 0.6164383561643836, 'f1': 0.6196213425129088, 'number': 584} | 0.6471 | 0.6404 | 0.6437 | 0.9123 |
102
+ | 0.0107 | 47.0 | 846 | 0.5057 | {'precision': 0.6730103806228374, 'recall': 0.666095890410959, 'f1': 0.6695352839931152, 'number': 584} | {'precision': 0.6245674740484429, 'recall': 0.6181506849315068, 'f1': 0.6213425129087781, 'number': 584} | 0.6488 | 0.6421 | 0.6454 | 0.9139 |
103
+ | 0.0127 | 48.0 | 864 | 0.5076 | {'precision': 0.6800699300699301, 'recall': 0.666095890410959, 'f1': 0.6730103806228375, 'number': 584} | {'precision': 0.6293706293706294, 'recall': 0.6164383561643836, 'f1': 0.6228373702422145, 'number': 584} | 0.6547 | 0.6413 | 0.6479 | 0.9156 |
104
+ | 0.0116 | 49.0 | 882 | 0.5185 | {'precision': 0.6759098786828422, 'recall': 0.6678082191780822, 'f1': 0.6718346253229973, 'number': 584} | {'precision': 0.6291161178509532, 'recall': 0.6215753424657534, 'f1': 0.6253229974160206, 'number': 584} | 0.6525 | 0.6447 | 0.6486 | 0.9148 |
105
+ | 0.0099 | 50.0 | 900 | 0.5142 | {'precision': 0.6764705882352942, 'recall': 0.6695205479452054, 'f1': 0.6729776247848538, 'number': 584} | {'precision': 0.629757785467128, 'recall': 0.6232876712328768, 'f1': 0.6265060240963856, 'number': 584} | 0.6531 | 0.6464 | 0.6497 | 0.9156 |
106
 
107
 
108
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