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bolu61
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logsegmenter

Token Classification
Transformers
Safetensors
roberta
Generated from Trainer
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  1. README.md +70 -105
  2. model.safetensors +1 -1
README.md CHANGED
@@ -2,6 +2,8 @@
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  library_name: transformers
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  tags:
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  - generated_from_trainer
 
 
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  model-index:
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  - name: sal-base
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  results: []
@@ -14,7 +16,38 @@ should probably proofread and complete it, then remove this comment. -->
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8697
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## Model description
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@@ -38,114 +71,46 @@ The following hyperparameters were used during training:
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  - eval_batch_size: 8
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  - seed: 45242
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  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- - lr_scheduler_type: cosine_with_restarts
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 100.0
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:-----:|:---------------:|
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- | 2.0797 | 1.0 | 807 | 1.8427 |
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- | 1.4525 | 2.0 | 1614 | 1.0320 |
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- | 1.0207 | 3.0 | 2421 | 0.8592 |
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- | 1.0664 | 4.0 | 3228 | 0.7038 |
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- | 0.9961 | 5.0 | 4035 | 0.5068 |
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- | 0.6692 | 6.0 | 4842 | 0.3971 |
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- | 0.3041 | 7.0 | 5649 | 0.3844 |
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- | 0.4348 | 8.0 | 6456 | 0.3507 |
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- | 0.3898 | 9.0 | 7263 | 0.3439 |
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- | 0.1955 | 10.0 | 8070 | 0.2859 |
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- | 0.3438 | 11.0 | 8877 | 0.3049 |
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- | 0.2301 | 12.0 | 9684 | 0.2657 |
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- | 0.1325 | 13.0 | 10491 | 0.2427 |
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- | 0.1481 | 14.0 | 11298 | 0.2547 |
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- | 0.0214 | 15.0 | 12105 | 0.2966 |
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- | 0.1104 | 16.0 | 12912 | 0.2886 |
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- | 0.065 | 17.0 | 13719 | 0.2805 |
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- | 0.1236 | 18.0 | 14526 | 0.2881 |
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- | 0.011 | 19.0 | 15333 | 0.2888 |
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- | 0.2482 | 20.0 | 16140 | 0.3615 |
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- | 0.1819 | 21.0 | 16947 | 0.3657 |
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- | 0.0461 | 22.0 | 17754 | 0.3575 |
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- | 0.1013 | 23.0 | 18561 | 0.3397 |
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- | 0.0623 | 24.0 | 19368 | 0.3244 |
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- | 0.0177 | 25.0 | 20175 | 0.3442 |
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- | 0.0085 | 26.0 | 20982 | 0.3931 |
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- | 0.034 | 27.0 | 21789 | 0.3658 |
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- | 0.0587 | 28.0 | 22596 | 0.3712 |
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- | 0.1045 | 29.0 | 23403 | 0.4020 |
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- | 0.0367 | 30.0 | 24210 | 0.5245 |
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- | 0.0688 | 31.0 | 25017 | 0.5180 |
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- | 0.0468 | 32.0 | 25824 | 0.3551 |
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- | 0.0226 | 33.0 | 26631 | 0.3973 |
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- | 0.0788 | 34.0 | 27438 | 0.4155 |
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- | 0.0628 | 35.0 | 28245 | 0.4288 |
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- | 0.0232 | 36.0 | 29052 | 0.4475 |
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- | 0.0148 | 37.0 | 29859 | 0.4464 |
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- | 0.1581 | 38.0 | 30666 | 0.5728 |
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- | 0.102 | 39.0 | 31473 | 0.4071 |
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- | 0.086 | 40.0 | 32280 | 0.4359 |
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- | 0.082 | 41.0 | 33087 | 0.3960 |
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- | 0.0338 | 42.0 | 33894 | 0.5187 |
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- | 0.0656 | 43.0 | 34701 | 0.5074 |
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- | 0.0546 | 44.0 | 35508 | 0.4921 |
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- | 0.006 | 45.0 | 36315 | 0.5108 |
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- | 0.0042 | 46.0 | 37122 | 0.5130 |
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- | 0.0541 | 47.0 | 37929 | 0.5102 |
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- | 0.0351 | 48.0 | 38736 | 0.4801 |
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- | 0.0082 | 49.0 | 39543 | 0.5563 |
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- | 0.1399 | 50.0 | 40350 | 0.5250 |
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- | 0.0371 | 51.0 | 41157 | 0.5732 |
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- | 0.0125 | 52.0 | 41964 | 0.6164 |
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- | 0.0729 | 53.0 | 42771 | 0.6178 |
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- | 0.0705 | 54.0 | 43578 | 0.6195 |
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- | 0.1058 | 55.0 | 44385 | 0.6180 |
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- | 0.1061 | 56.0 | 45192 | 0.6778 |
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- | 0.1624 | 57.0 | 45999 | 0.6777 |
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- | 0.0078 | 58.0 | 46806 | 0.5889 |
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- | 0.0101 | 59.0 | 47613 | 0.6608 |
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- | 0.0125 | 60.0 | 48420 | 0.6582 |
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- | 0.0084 | 61.0 | 49227 | 0.6625 |
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- | 0.0632 | 62.0 | 50034 | 0.6881 |
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- | 0.0104 | 63.0 | 50841 | 0.6781 |
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- | 0.0104 | 64.0 | 51648 | 0.6790 |
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- | 0.0188 | 65.0 | 52455 | 0.6319 |
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- | 0.0369 | 66.0 | 53262 | 0.6444 |
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- | 0.0042 | 67.0 | 54069 | 0.7006 |
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- | 0.0615 | 68.0 | 54876 | 0.6862 |
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- | 0.0585 | 69.0 | 55683 | 0.6895 |
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- | 0.0033 | 70.0 | 56490 | 0.7316 |
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- | 0.0458 | 71.0 | 57297 | 0.7493 |
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- | 0.0462 | 72.0 | 58104 | 0.7519 |
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- | 0.0081 | 73.0 | 58911 | 0.7512 |
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- | 0.0234 | 74.0 | 59718 | 0.6921 |
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- | 0.013 | 75.0 | 60525 | 0.7668 |
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- | 0.0438 | 76.0 | 61332 | 0.7913 |
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- | 0.0117 | 77.0 | 62139 | 0.7236 |
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- | 0.0658 | 78.0 | 62946 | 0.7462 |
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- | 0.007 | 79.0 | 63753 | 0.7387 |
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- | 0.0177 | 80.0 | 64560 | 0.7444 |
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- | 0.0052 | 81.0 | 65367 | 0.7462 |
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- | 0.0005 | 82.0 | 66174 | 0.7463 |
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- | 0.005 | 83.0 | 66981 | 0.8667 |
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- | 0.0824 | 84.0 | 67788 | 0.7736 |
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- | 0.0067 | 85.0 | 68595 | 0.7529 |
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- | 0.014 | 86.0 | 69402 | 0.7829 |
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- | 0.0019 | 87.0 | 70209 | 0.8120 |
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- | 0.0091 | 88.0 | 71016 | 0.8180 |
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- | 0.0039 | 89.0 | 71823 | 0.8255 |
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- | 0.0085 | 90.0 | 72630 | 0.8275 |
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- | 0.0019 | 91.0 | 73437 | 0.8279 |
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- | 0.0419 | 92.0 | 74244 | 0.8148 |
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- | 0.0182 | 93.0 | 75051 | 0.8169 |
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- | 0.0152 | 94.0 | 75858 | 0.8195 |
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- | 0.0044 | 95.0 | 76665 | 0.8245 |
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- | 0.0027 | 96.0 | 77472 | 0.8645 |
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- | 0.0161 | 97.0 | 78279 | 0.8314 |
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- | 0.0028 | 98.0 | 79086 | 0.8691 |
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- | 0.0141 | 99.0 | 79893 | 0.8696 |
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- | 0.0053 | 100.0 | 80700 | 0.8697 |
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  ### Framework versions
 
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  library_name: transformers
3
  tags:
4
  - generated_from_trainer
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+ metrics:
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+ - accuracy
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  model-index:
8
  - name: sal-base
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  results: []
 
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  This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4904
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+ - Accuracy: 0.9313
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+ - Precision Eol: 0.9398
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+ - Precision Msg: 0.8710
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+ - Precision Cmd: 0.0
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+ - Precision Var: 1.0
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+ - Precision Dff: 0.9469
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+ - Precision Pgr: 0.65
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+ - Precision Stk: 1.0
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+ - Precision Itm: 0.9667
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+ - Precision Hex: 0.6
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+ - Precision Yml: 1.0
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+ - Recall Eol: 0.9713
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+ - Recall Msg: 0.9643
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+ - Recall Cmd: 0.0
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+ - Recall Var: 0.75
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+ - Recall Dff: 0.9774
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+ - Recall Pgr: 0.9286
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+ - Recall Stk: 0.7671
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+ - Recall Itm: 0.7838
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+ - Recall Hex: 1.0
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+ - Recall Yml: 1.0
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+ - F1 Eol: 0.9553
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+ - F1 Msg: 0.9153
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+ - F1 Cmd: 0.0
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+ - F1 Var: 0.8571
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+ - F1 Dff: 0.9619
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+ - F1 Pgr: 0.7647
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+ - F1 Stk: 0.8682
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+ - F1 Itm: 0.8657
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+ - F1 Hex: 0.75
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+ - F1 Yml: 1.0
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52
  ## Model description
53
 
 
71
  - eval_batch_size: 8
72
  - seed: 45242
73
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 32.0
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision Eol | Precision Msg | Precision Cmd | Precision Var | Precision Dff | Precision Pgr | Precision Stk | Precision Itm | Precision Hex | Precision Yml | Recall Eol | Recall Msg | Recall Cmd | Recall Var | Recall Dff | Recall Pgr | Recall Stk | Recall Itm | Recall Hex | Recall Yml | F1 Eol | F1 Msg | F1 Cmd | F1 Var | F1 Dff | F1 Pgr | F1 Stk | F1 Itm | F1 Hex | F1 Yml |
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+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|:-------------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:----------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|
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+ | 1.3346 | 1.0 | 807 | 1.1337 | 0.6295 | 0.4384 | 0.0 | 0.0 | 0.0 | 0.9043 | 0.0 | 0.7 | 0.0 | 0.0 | 0.0 | 0.8517 | 0.0 | 0.0 | 0.0 | 0.8226 | 0.0 | 0.0959 | 0.0 | 0.0 | 0.0 | 0.5789 | 0.0 | 0.0 | 0.0 | 0.8615 | 0.0 | 0.1687 | 0.0 | 0.0 | 0.0 |
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+ | 1.1568 | 2.0 | 1614 | 0.6844 | 0.7868 | 0.6988 | 0.8571 | 0.0 | 0.0 | 0.9900 | 0.8 | 0.4766 | 0.8333 | 0.0 | 0.0 | 0.8325 | 0.2143 | 0.0 | 0.0 | 0.9548 | 0.5714 | 0.8356 | 0.1351 | 0.0 | 0.0 | 0.7598 | 0.3429 | 0.0 | 0.0 | 0.9721 | 0.6667 | 0.6070 | 0.2326 | 0.0 | 0.0 |
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+ | 0.7174 | 3.0 | 2421 | 0.6051 | 0.8498 | 0.7316 | 0.9091 | 0.0 | 0.0 | 0.9966 | 0.56 | 0.7846 | 0.8387 | 0.0 | 0.0 | 0.9522 | 0.3571 | 0.0 | 0.0 | 0.9484 | 1.0 | 0.6986 | 0.7027 | 0.0 | 0.0 | 0.8274 | 0.5128 | 0.0 | 0.0 | 0.9719 | 0.7179 | 0.7391 | 0.7647 | 0.0 | 0.0 |
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+ | 0.7051 | 4.0 | 3228 | 0.4208 | 0.9013 | 0.8417 | 0.8235 | 0.0 | 0.0 | 0.9870 | 0.5417 | 0.9 | 1.0 | 0.0 | 0.8889 | 0.9665 | 0.5 | 0.0 | 0.0 | 0.9806 | 0.9286 | 0.8630 | 0.7027 | 0.0 | 1.0 | 0.8998 | 0.6222 | 0.0 | 0.0 | 0.9838 | 0.6842 | 0.8811 | 0.8254 | 0.0 | 0.9412 |
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+ | 0.5254 | 5.0 | 4035 | 0.3691 | 0.9142 | 0.8826 | 0.7 | 0.0 | 0.0 | 0.9902 | 0.5417 | 0.9103 | 1.0 | 0.0 | 1.0 | 0.9713 | 0.5 | 0.0 | 0.0 | 0.9806 | 0.9286 | 0.9726 | 0.7027 | 0.0 | 1.0 | 0.9248 | 0.5833 | 0.0 | 0.0 | 0.9854 | 0.6842 | 0.9404 | 0.8254 | 0.0 | 1.0 |
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+ | 0.2888 | 6.0 | 4842 | 0.3166 | 0.9256 | 0.9615 | 0.7407 | 0.0 | 0.0 | 0.9902 | 0.56 | 0.8295 | 0.9655 | 0.0 | 0.8889 | 0.9569 | 0.7143 | 0.0 | 0.0 | 0.9806 | 1.0 | 1.0 | 0.7568 | 0.0 | 1.0 | 0.9592 | 0.7273 | 0.0 | 0.0 | 0.9854 | 0.7179 | 0.9068 | 0.8485 | 0.0 | 0.9412 |
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+ | 0.1577 | 7.0 | 5649 | 0.3385 | 0.9299 | 0.9309 | 0.7857 | 0.0 | 0.0 | 0.9870 | 0.5652 | 0.9125 | 0.9655 | 0.0 | 1.0 | 0.9665 | 0.7857 | 0.0 | 0.0 | 0.9806 | 0.9286 | 1.0 | 0.7568 | 0.0 | 1.0 | 0.9484 | 0.7857 | 0.0 | 0.0 | 0.9838 | 0.7027 | 0.9542 | 0.8485 | 0.0 | 1.0 |
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+ | 0.2253 | 8.0 | 6456 | 0.3227 | 0.9356 | 0.9528 | 0.8438 | 0.0 | 0.0 | 0.9967 | 0.56 | 0.8588 | 1.0 | 0.0 | 1.0 | 0.9665 | 0.9643 | 0.0 | 0.0 | 0.9774 | 1.0 | 1.0 | 0.7297 | 0.0 | 1.0 | 0.9596 | 0.9 | 0.0 | 0.0 | 0.9870 | 0.7179 | 0.9241 | 0.8438 | 0.0 | 1.0 |
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+ | 0.2967 | 9.0 | 7263 | 0.2755 | 0.9456 | 0.9484 | 0.8710 | 0.0 | 0.0 | 0.9934 | 0.5909 | 0.9241 | 1.0 | 0.5 | 1.0 | 0.9665 | 0.9643 | 0.0 | 0.0 | 0.9774 | 0.9286 | 1.0 | 0.7838 | 0.6667 | 1.0 | 0.9573 | 0.9153 | 0.0 | 0.0 | 0.9854 | 0.7222 | 0.9605 | 0.8788 | 0.5714 | 1.0 |
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+ | 0.0673 | 10.0 | 8070 | 0.2925 | 0.9485 | 0.9528 | 0.8710 | 0.0 | 0.0 | 0.9838 | 0.56 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9665 | 0.9643 | 0.0 | 0.0 | 0.9806 | 1.0 | 0.9863 | 0.7297 | 1.0 | 1.0 | 0.9596 | 0.9153 | 0.0 | 0.0 | 0.9822 | 0.7179 | 0.9931 | 0.8438 | 0.75 | 1.0 |
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+ | 0.2369 | 11.0 | 8877 | 0.3057 | 0.9514 | 0.9533 | 0.9 | 0.0 | 0.0 | 0.9870 | 0.5417 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9761 | 0.9643 | 0.0 | 0.0 | 0.9806 | 0.9286 | 0.9863 | 0.7568 | 1.0 | 1.0 | 0.9645 | 0.9310 | 0.0 | 0.0 | 0.9838 | 0.6842 | 0.9931 | 0.8615 | 0.75 | 1.0 |
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+ | 0.1307 | 12.0 | 9684 | 0.3090 | 0.9499 | 0.9531 | 0.8710 | 0.0 | 0.0 | 0.9870 | 0.5417 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.0 | 0.9774 | 0.9286 | 1.0 | 0.7568 | 1.0 | 1.0 | 0.9621 | 0.9153 | 0.0 | 0.0 | 0.9822 | 0.6842 | 1.0 | 0.8615 | 0.75 | 1.0 |
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+ | 0.0639 | 13.0 | 10491 | 0.2790 | 0.9642 | 0.9758 | 0.875 | 0.0 | 1.0 | 0.9935 | 0.6190 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9665 | 1.0 | 0.0 | 0.75 | 0.9935 | 0.9286 | 1.0 | 0.8108 | 1.0 | 1.0 | 0.9712 | 0.9333 | 0.0 | 0.8571 | 0.9935 | 0.7429 | 1.0 | 0.8955 | 0.75 | 1.0 |
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+ | 0.1262 | 14.0 | 11298 | 0.3562 | 0.9342 | 0.9486 | 0.9 | 0.0 | 1.0 | 0.9441 | 0.6190 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 0.9286 | 0.7671 | 0.8108 | 1.0 | 1.0 | 0.9598 | 0.9310 | 0.0 | 0.8571 | 0.9620 | 0.7429 | 0.8682 | 0.8955 | 0.75 | 1.0 |
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+ | 0.0169 | 15.0 | 12105 | 0.3680 | 0.9557 | 0.9442 | 0.8710 | 0.0 | 1.0 | 0.9967 | 0.6190 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9774 | 0.9286 | 1.0 | 0.7838 | 1.0 | 1.0 | 0.9575 | 0.9153 | 0.0 | 0.8571 | 0.9870 | 0.7429 | 1.0 | 0.8788 | 0.75 | 1.0 |
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+ | 0.1178 | 16.0 | 12912 | 0.3159 | 0.9571 | 0.9531 | 0.8710 | 0.0 | 1.0 | 0.9967 | 0.5909 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9839 | 0.9286 | 1.0 | 0.7568 | 1.0 | 1.0 | 0.9621 | 0.9153 | 0.0 | 0.8571 | 0.9903 | 0.7222 | 1.0 | 0.8615 | 0.75 | 1.0 |
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+ | 0.1505 | 17.0 | 13719 | 0.3400 | 0.9571 | 0.9486 | 0.8710 | 0.0 | 1.0 | 0.9967 | 0.6364 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9774 | 1.0 | 1.0 | 0.7838 | 1.0 | 1.0 | 0.9598 | 0.9153 | 0.0 | 0.8571 | 0.9870 | 0.7778 | 1.0 | 0.8788 | 0.75 | 1.0 |
99
+ | 0.0759 | 18.0 | 14526 | 0.4036 | 0.9385 | 0.9621 | 0.8710 | 0.0 | 1.0 | 0.9474 | 0.6364 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9871 | 1.0 | 0.7671 | 0.8108 | 1.0 | 1.0 | 0.9667 | 0.9153 | 0.0 | 0.8571 | 0.9668 | 0.7778 | 0.8682 | 0.8955 | 0.75 | 1.0 |
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+ | 0.023 | 19.0 | 15333 | 0.4086 | 0.9542 | 0.9398 | 0.8710 | 0.0 | 1.0 | 0.9967 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9774 | 0.9286 | 0.9863 | 0.7838 | 1.0 | 1.0 | 0.9553 | 0.9153 | 0.0 | 0.8571 | 0.9870 | 0.7647 | 0.9931 | 0.8657 | 0.75 | 1.0 |
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+ | 0.0844 | 20.0 | 16140 | 0.4447 | 0.9342 | 0.9486 | 0.8710 | 0.0 | 1.0 | 0.9470 | 0.6364 | 1.0 | 1.0 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 1.0 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9598 | 0.9153 | 0.0 | 0.8571 | 0.9635 | 0.7778 | 0.8682 | 0.8788 | 0.75 | 1.0 |
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+ | 0.1371 | 21.0 | 16947 | 0.4818 | 0.9299 | 0.9401 | 0.9 | 0.0 | 1.0 | 0.9410 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9761 | 0.9643 | 0.0 | 0.25 | 0.9774 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9577 | 0.9310 | 0.0 | 0.4 | 0.9589 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
103
+ | 0.0311 | 22.0 | 17754 | 0.4369 | 0.9356 | 0.9531 | 0.8710 | 0.0 | 1.0 | 0.9472 | 0.6667 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9839 | 1.0 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9621 | 0.9153 | 0.0 | 0.8571 | 0.9652 | 0.8 | 0.8682 | 0.8657 | 0.75 | 1.0 |
104
+ | 0.0343 | 23.0 | 18561 | 0.4735 | 0.9342 | 0.9486 | 0.875 | 0.0 | 1.0 | 0.9469 | 0.6667 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 1.0 | 0.0 | 0.75 | 0.9774 | 1.0 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9598 | 0.9333 | 0.0 | 0.8571 | 0.9619 | 0.8 | 0.8682 | 0.8657 | 0.75 | 1.0 |
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+ | 0.0752 | 24.0 | 19368 | 0.4295 | 0.9356 | 0.9531 | 0.875 | 0.0 | 1.0 | 0.9470 | 0.6667 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 1.0 | 0.0 | 0.75 | 0.9806 | 1.0 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9621 | 0.9333 | 0.0 | 0.8571 | 0.9635 | 0.8 | 0.8682 | 0.8657 | 0.75 | 1.0 |
106
+ | 0.0074 | 25.0 | 20175 | 0.4687 | 0.9313 | 0.9398 | 0.8710 | 0.0 | 1.0 | 0.9469 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9774 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9553 | 0.9153 | 0.0 | 0.8571 | 0.9619 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
107
+ | 0.0053 | 26.0 | 20982 | 0.4892 | 0.9328 | 0.9442 | 0.8710 | 0.0 | 1.0 | 0.9470 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9575 | 0.9153 | 0.0 | 0.8571 | 0.9635 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
108
+ | 0.0211 | 27.0 | 21789 | 0.4765 | 0.9328 | 0.9442 | 0.8710 | 0.0 | 1.0 | 0.9470 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9575 | 0.9153 | 0.0 | 0.8571 | 0.9635 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
109
+ | 0.0671 | 28.0 | 22596 | 0.4978 | 0.9328 | 0.9442 | 0.8710 | 0.0 | 1.0 | 0.9470 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9575 | 0.9153 | 0.0 | 0.8571 | 0.9635 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
110
+ | 0.0065 | 29.0 | 23403 | 0.4934 | 0.9328 | 0.9442 | 0.8710 | 0.0 | 1.0 | 0.9470 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9575 | 0.9153 | 0.0 | 0.8571 | 0.9635 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
111
+ | 0.0003 | 30.0 | 24210 | 0.4905 | 0.9328 | 0.9442 | 0.8710 | 0.0 | 1.0 | 0.9470 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9806 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9575 | 0.9153 | 0.0 | 0.8571 | 0.9635 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
112
+ | 0.0095 | 31.0 | 25017 | 0.4895 | 0.9313 | 0.9398 | 0.8710 | 0.0 | 1.0 | 0.9469 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9774 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9553 | 0.9153 | 0.0 | 0.8571 | 0.9619 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
113
+ | 0.0665 | 32.0 | 25824 | 0.4904 | 0.9313 | 0.9398 | 0.8710 | 0.0 | 1.0 | 0.9469 | 0.65 | 1.0 | 0.9667 | 0.6 | 1.0 | 0.9713 | 0.9643 | 0.0 | 0.75 | 0.9774 | 0.9286 | 0.7671 | 0.7838 | 1.0 | 1.0 | 0.9553 | 0.9153 | 0.0 | 0.8571 | 0.9619 | 0.7647 | 0.8682 | 0.8657 | 0.75 | 1.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
114
 
115
 
116
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