Hugging Face's logo

brandonRivas
/
roberta-large-ner-qlorafinetune-runs-colab

PEFT
TensorBoard
Safetensors
Generated from Trainer
Model card Files Metrics Community
brandonRivas commited on
Commit
a883a5f
·
verified ·
1 Parent(s): 38e2883

End of training

Browse files
Files changed (1) hide show
  1. README.md +98 -98
README.md CHANGED
@@ -23,11 +23,11 @@ should probably proofread and complete it, then remove this comment. -->
23
 
24
  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the biobert_json dataset.
25
  It achieves the following results on the evaluation set:
26
- - Loss: 0.0747
27
- - Precision: 0.9341
28
- - Recall: 0.9552
29
- - F1: 0.9446
30
- - Accuracy: 0.9805
31
 
32
  ## Model description
33
 
@@ -47,8 +47,8 @@ More information needed
47
 
48
  The following hyperparameters were used during training:
49
  - learning_rate: 0.0004
50
- - train_batch_size: 32
51
- - eval_batch_size: 32
52
  - seed: 42
53
  - optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54
  - lr_scheduler_type: linear
@@ -59,97 +59,97 @@ The following hyperparameters were used during training:
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
61
  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
62
- | 2.3591 | 0.0654 | 20 | 1.1618 | 0.0 | 0.0 | 0.0 | 0.7196 |
63
- | 1.016 | 0.1307 | 40 | 0.5998 | 0.5713 | 0.5601 | 0.5657 | 0.8528 |
64
- | 0.5032 | 0.1961 | 60 | 0.2553 | 0.8199 | 0.8139 | 0.8169 | 0.9357 |
65
- | 0.3019 | 0.2614 | 80 | 0.1630 | 0.8376 | 0.8817 | 0.8591 | 0.9522 |
66
- | 0.2149 | 0.3268 | 100 | 0.1543 | 0.8341 | 0.9190 | 0.8745 | 0.9557 |
67
- | 0.2131 | 0.3922 | 120 | 0.1331 | 0.8587 | 0.9157 | 0.8863 | 0.9592 |
68
- | 0.1722 | 0.4575 | 140 | 0.1217 | 0.9150 | 0.8981 | 0.9065 | 0.9660 |
69
- | 0.1646 | 0.5229 | 160 | 0.1060 | 0.8982 | 0.9465 | 0.9217 | 0.9711 |
70
- | 0.1663 | 0.5882 | 180 | 0.1212 | 0.8900 | 0.9454 | 0.9169 | 0.9684 |
71
- | 0.1316 | 0.6536 | 200 | 0.0979 | 0.9071 | 0.9409 | 0.9237 | 0.9713 |
72
- | 0.1342 | 0.7190 | 220 | 0.0846 | 0.9123 | 0.9382 | 0.9251 | 0.9743 |
73
- | 0.1334 | 0.7843 | 240 | 0.0919 | 0.9141 | 0.9491 | 0.9313 | 0.9743 |
74
- | 0.1124 | 0.8497 | 260 | 0.0927 | 0.9143 | 0.9405 | 0.9272 | 0.9735 |
75
- | 0.124 | 0.9150 | 280 | 0.0989 | 0.9047 | 0.9457 | 0.9247 | 0.9710 |
76
- | 0.1295 | 0.9804 | 300 | 0.0898 | 0.9121 | 0.9302 | 0.9211 | 0.9730 |
77
- | 0.1102 | 1.0458 | 320 | 0.0894 | 0.9060 | 0.9417 | 0.9235 | 0.9730 |
78
- | 0.0943 | 1.1111 | 340 | 0.1187 | 0.9132 | 0.9434 | 0.9281 | 0.9722 |
79
- | 0.1055 | 1.1765 | 360 | 0.1075 | 0.8977 | 0.9473 | 0.9218 | 0.9690 |
80
- | 0.1003 | 1.2418 | 380 | 0.0876 | 0.9193 | 0.9471 | 0.9330 | 0.9754 |
81
- | 0.1073 | 1.3072 | 400 | 0.0774 | 0.9259 | 0.9526 | 0.9391 | 0.9784 |
82
- | 0.1176 | 1.3725 | 420 | 0.0986 | 0.8830 | 0.9363 | 0.9089 | 0.9692 |
83
- | 0.1028 | 1.4379 | 440 | 0.0778 | 0.9318 | 0.9504 | 0.9410 | 0.9785 |
84
- | 0.0953 | 1.5033 | 460 | 0.0747 | 0.9294 | 0.9527 | 0.9409 | 0.9783 |
85
- | 0.1023 | 1.5686 | 480 | 0.0757 | 0.9263 | 0.9532 | 0.9395 | 0.9779 |
86
- | 0.0865 | 1.6340 | 500 | 0.0884 | 0.9057 | 0.9469 | 0.9258 | 0.9738 |
87
- | 0.0744 | 1.6993 | 520 | 0.0889 | 0.9045 | 0.9654 | 0.9339 | 0.9752 |
88
- | 0.0779 | 1.7647 | 540 | 0.0792 | 0.9176 | 0.9402 | 0.9288 | 0.9761 |
89
- | 0.0946 | 1.8301 | 560 | 0.0821 | 0.9139 | 0.9548 | 0.9339 | 0.9761 |
90
- | 0.0966 | 1.8954 | 580 | 0.1007 | 0.9029 | 0.9552 | 0.9283 | 0.9715 |
91
- | 0.098 | 1.9608 | 600 | 0.0960 | 0.9137 | 0.9460 | 0.9296 | 0.9737 |
92
- | 0.0829 | 2.0261 | 620 | 0.0859 | 0.9232 | 0.9514 | 0.9371 | 0.9766 |
93
- | 0.077 | 2.0915 | 640 | 0.0821 | 0.9196 | 0.9575 | 0.9382 | 0.9768 |
94
- | 0.0598 | 2.1569 | 660 | 0.0756 | 0.9226 | 0.9490 | 0.9356 | 0.9771 |
95
- | 0.0864 | 2.2222 | 680 | 0.0768 | 0.9240 | 0.9560 | 0.9397 | 0.9777 |
96
- | 0.0836 | 2.2876 | 700 | 0.0846 | 0.9175 | 0.9577 | 0.9372 | 0.9762 |
97
- | 0.0629 | 2.3529 | 720 | 0.0706 | 0.9355 | 0.9513 | 0.9433 | 0.9796 |
98
- | 0.0667 | 2.4183 | 740 | 0.0781 | 0.9273 | 0.9527 | 0.9398 | 0.9779 |
99
- | 0.09 | 2.4837 | 760 | 0.0728 | 0.9297 | 0.9615 | 0.9453 | 0.9802 |
100
- | 0.0718 | 2.5490 | 780 | 0.0772 | 0.9338 | 0.9609 | 0.9471 | 0.9808 |
101
- | 0.0765 | 2.6144 | 800 | 0.0712 | 0.9403 | 0.9558 | 0.9480 | 0.9810 |
102
- | 0.0632 | 2.6797 | 820 | 0.0759 | 0.9377 | 0.9512 | 0.9444 | 0.9795 |
103
- | 0.0667 | 2.7451 | 840 | 0.0787 | 0.9168 | 0.9484 | 0.9323 | 0.9774 |
104
- | 0.0652 | 2.8105 | 860 | 0.0754 | 0.9320 | 0.9587 | 0.9452 | 0.9804 |
105
- | 0.0704 | 2.8758 | 880 | 0.0715 | 0.9335 | 0.9576 | 0.9454 | 0.9802 |
106
- | 0.0583 | 2.9412 | 900 | 0.0744 | 0.9227 | 0.9587 | 0.9404 | 0.9789 |
107
- | 0.0589 | 3.0065 | 920 | 0.0710 | 0.9334 | 0.9610 | 0.9470 | 0.9810 |
108
- | 0.0489 | 3.0719 | 940 | 0.0720 | 0.9342 | 0.9583 | 0.9461 | 0.9809 |
109
- | 0.0545 | 3.1373 | 960 | 0.0886 | 0.9170 | 0.9551 | 0.9357 | 0.9765 |
110
- | 0.0491 | 3.2026 | 980 | 0.0738 | 0.9353 | 0.9551 | 0.9451 | 0.9802 |
111
- | 0.0563 | 3.2680 | 1000 | 0.0741 | 0.9308 | 0.9544 | 0.9424 | 0.9794 |
112
- | 0.0527 | 3.3333 | 1020 | 0.0755 | 0.9257 | 0.9525 | 0.9389 | 0.9785 |
113
- | 0.0525 | 3.3987 | 1040 | 0.0800 | 0.9218 | 0.9655 | 0.9432 | 0.9790 |
114
- | 0.0599 | 3.4641 | 1060 | 0.0838 | 0.9190 | 0.9543 | 0.9363 | 0.9777 |
115
- | 0.0474 | 3.5294 | 1080 | 0.0770 | 0.9267 | 0.9497 | 0.9381 | 0.9790 |
116
- | 0.0508 | 3.5948 | 1100 | 0.0821 | 0.9293 | 0.9577 | 0.9433 | 0.9780 |
117
- | 0.048 | 3.6601 | 1120 | 0.0739 | 0.9360 | 0.9527 | 0.9443 | 0.9802 |
118
- | 0.0592 | 3.7255 | 1140 | 0.0733 | 0.9374 | 0.9611 | 0.9491 | 0.9810 |
119
- | 0.0546 | 3.7908 | 1160 | 0.0721 | 0.9389 | 0.9575 | 0.9481 | 0.9814 |
120
- | 0.0668 | 3.8562 | 1180 | 0.0773 | 0.9278 | 0.9581 | 0.9427 | 0.9792 |
121
- | 0.0626 | 3.9216 | 1200 | 0.0816 | 0.9280 | 0.9567 | 0.9421 | 0.9783 |
122
- | 0.0664 | 3.9869 | 1220 | 0.0720 | 0.9332 | 0.9577 | 0.9453 | 0.9806 |
123
- | 0.0465 | 4.0523 | 1240 | 0.0743 | 0.9350 | 0.9579 | 0.9463 | 0.9804 |
124
- | 0.0389 | 4.1176 | 1260 | 0.0742 | 0.9279 | 0.9583 | 0.9429 | 0.9802 |
125
- | 0.0412 | 4.1830 | 1280 | 0.0720 | 0.9382 | 0.9572 | 0.9476 | 0.9816 |
126
- | 0.0451 | 4.2484 | 1300 | 0.0749 | 0.9327 | 0.9514 | 0.9419 | 0.9799 |
127
- | 0.0455 | 4.3137 | 1320 | 0.0732 | 0.9399 | 0.9494 | 0.9446 | 0.9807 |
128
- | 0.0474 | 4.3791 | 1340 | 0.0731 | 0.9349 | 0.9569 | 0.9458 | 0.9805 |
129
- | 0.0414 | 4.4444 | 1360 | 0.0749 | 0.9312 | 0.9558 | 0.9434 | 0.9800 |
130
- | 0.0338 | 4.5098 | 1380 | 0.0774 | 0.9305 | 0.9576 | 0.9438 | 0.9799 |
131
- | 0.0495 | 4.5752 | 1400 | 0.0774 | 0.9286 | 0.9501 | 0.9392 | 0.9794 |
132
- | 0.0442 | 4.6405 | 1420 | 0.0751 | 0.9370 | 0.9611 | 0.9489 | 0.9813 |
133
- | 0.0376 | 4.7059 | 1440 | 0.0819 | 0.9255 | 0.9532 | 0.9392 | 0.9778 |
134
- | 0.0466 | 4.7712 | 1460 | 0.0768 | 0.9373 | 0.9566 | 0.9468 | 0.9805 |
135
- | 0.0407 | 4.8366 | 1480 | 0.0763 | 0.9359 | 0.9574 | 0.9465 | 0.9803 |
136
- | 0.0419 | 4.9020 | 1500 | 0.0769 | 0.9310 | 0.9570 | 0.9438 | 0.9796 |
137
- | 0.0521 | 4.9673 | 1520 | 0.0743 | 0.9336 | 0.9522 | 0.9428 | 0.9796 |
138
- | 0.0356 | 5.0327 | 1540 | 0.0793 | 0.9271 | 0.9544 | 0.9406 | 0.9788 |
139
- | 0.0359 | 5.0980 | 1560 | 0.0744 | 0.9386 | 0.9574 | 0.9479 | 0.9807 |
140
- | 0.0411 | 5.1634 | 1580 | 0.0749 | 0.9354 | 0.9592 | 0.9472 | 0.9806 |
141
- | 0.036 | 5.2288 | 1600 | 0.0764 | 0.9322 | 0.9518 | 0.9419 | 0.9799 |
142
- | 0.0316 | 5.2941 | 1620 | 0.0777 | 0.9287 | 0.9531 | 0.9408 | 0.9788 |
143
- | 0.0314 | 5.3595 | 1640 | 0.0756 | 0.9330 | 0.9568 | 0.9447 | 0.9802 |
144
- | 0.0321 | 5.4248 | 1660 | 0.0727 | 0.9405 | 0.9569 | 0.9486 | 0.9815 |
145
- | 0.0427 | 5.4902 | 1680 | 0.0728 | 0.9381 | 0.9570 | 0.9474 | 0.9810 |
146
- | 0.031 | 5.5556 | 1700 | 0.0718 | 0.9414 | 0.9573 | 0.9493 | 0.9817 |
147
- | 0.033 | 5.6209 | 1720 | 0.0752 | 0.9324 | 0.9562 | 0.9442 | 0.9800 |
148
- | 0.0342 | 5.6863 | 1740 | 0.0742 | 0.9367 | 0.9545 | 0.9455 | 0.9804 |
149
- | 0.0348 | 5.7516 | 1760 | 0.0748 | 0.9328 | 0.9554 | 0.9439 | 0.9800 |
150
- | 0.0295 | 5.8170 | 1780 | 0.0750 | 0.9326 | 0.9561 | 0.9442 | 0.9802 |
151
- | 0.035 | 5.8824 | 1800 | 0.0752 | 0.9328 | 0.9560 | 0.9443 | 0.9803 |
152
- | 0.0285 | 5.9477 | 1820 | 0.0747 | 0.9341 | 0.9552 | 0.9446 | 0.9805 |
153
 
154
 
155
  ### Framework versions
 
23
 
24
  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the biobert_json dataset.
25
  It achieves the following results on the evaluation set:
26
+ - Loss: 0.0742
27
+ - Precision: 0.9394
28
+ - Recall: 0.9563
29
+ - F1: 0.9478
30
+ - Accuracy: 0.9810
31
 
32
  ## Model description
33
 
 
47
 
48
  The following hyperparameters were used during training:
49
  - learning_rate: 0.0004
50
+ - train_batch_size: 16
51
+ - eval_batch_size: 16
52
  - seed: 42
53
  - optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
54
  - lr_scheduler_type: linear
 
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
61
  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
62
+ | 0.0513 | 0.0327 | 20 | 0.0990 | 0.9421 | 0.9307 | 0.9364 | 0.9776 |
63
+ | 0.0862 | 0.0654 | 40 | 0.1131 | 0.9052 | 0.9417 | 0.9231 | 0.9730 |
64
+ | 0.0883 | 0.0980 | 60 | 0.1008 | 0.9070 | 0.9417 | 0.9240 | 0.9736 |
65
+ | 0.0779 | 0.1307 | 80 | 0.1018 | 0.9014 | 0.9447 | 0.9226 | 0.9733 |
66
+ | 0.1107 | 0.1634 | 100 | 0.1126 | 0.9109 | 0.9451 | 0.9277 | 0.9705 |
67
+ | 0.1039 | 0.1961 | 120 | 0.0843 | 0.9291 | 0.9451 | 0.9370 | 0.9770 |
68
+ | 0.0875 | 0.2288 | 140 | 0.0921 | 0.9127 | 0.9422 | 0.9272 | 0.9739 |
69
+ | 0.0838 | 0.2614 | 160 | 0.0949 | 0.9208 | 0.9555 | 0.9378 | 0.9765 |
70
+ | 0.0785 | 0.2941 | 180 | 0.0847 | 0.9176 | 0.9549 | 0.9359 | 0.9768 |
71
+ | 0.0752 | 0.3268 | 200 | 0.0989 | 0.9068 | 0.9497 | 0.9277 | 0.9721 |
72
+ | 0.0891 | 0.3595 | 220 | 0.0990 | 0.9014 | 0.9555 | 0.9277 | 0.9738 |
73
+ | 0.1096 | 0.3922 | 240 | 0.0907 | 0.9073 | 0.9583 | 0.9321 | 0.9746 |
74
+ | 0.1101 | 0.4248 | 260 | 0.0848 | 0.9137 | 0.9500 | 0.9315 | 0.9754 |
75
+ | 0.0745 | 0.4575 | 280 | 0.0824 | 0.9126 | 0.9384 | 0.9253 | 0.9751 |
76
+ | 0.0778 | 0.4902 | 300 | 0.0802 | 0.9271 | 0.9561 | 0.9414 | 0.9785 |
77
+ | 0.0823 | 0.5229 | 320 | 0.0955 | 0.9030 | 0.9402 | 0.9212 | 0.9732 |
78
+ | 0.0866 | 0.5556 | 340 | 0.1133 | 0.8918 | 0.9252 | 0.9082 | 0.9667 |
79
+ | 0.0855 | 0.5882 | 360 | 0.0853 | 0.9205 | 0.9564 | 0.9381 | 0.9777 |
80
+ | 0.0819 | 0.6209 | 380 | 0.0891 | 0.9162 | 0.9543 | 0.9349 | 0.9760 |
81
+ | 0.0646 | 0.6536 | 400 | 0.0872 | 0.9127 | 0.9473 | 0.9297 | 0.9757 |
82
+ | 0.0661 | 0.6863 | 420 | 0.0943 | 0.9177 | 0.9561 | 0.9365 | 0.9768 |
83
+ | 0.0802 | 0.7190 | 440 | 0.0892 | 0.9392 | 0.9363 | 0.9378 | 0.9771 |
84
+ | 0.0736 | 0.7516 | 460 | 0.0833 | 0.9204 | 0.9421 | 0.9311 | 0.9759 |
85
+ | 0.0838 | 0.7843 | 480 | 0.0835 | 0.9255 | 0.9622 | 0.9435 | 0.9780 |
86
+ | 0.0756 | 0.8170 | 500 | 0.0805 | 0.9302 | 0.9491 | 0.9396 | 0.9781 |
87
+ | 0.0431 | 0.8497 | 520 | 0.0924 | 0.9184 | 0.9560 | 0.9368 | 0.9771 |
88
+ | 0.0708 | 0.8824 | 540 | 0.0833 | 0.9225 | 0.9540 | 0.9380 | 0.9774 |
89
+ | 0.0796 | 0.9150 | 560 | 0.0883 | 0.9104 | 0.9476 | 0.9286 | 0.9754 |
90
+ | 0.0826 | 0.9477 | 580 | 0.0792 | 0.9200 | 0.9616 | 0.9403 | 0.9786 |
91
+ | 0.091 | 0.9804 | 600 | 0.0832 | 0.9324 | 0.9531 | 0.9426 | 0.9780 |
92
+ | 0.0818 | 1.0131 | 620 | 0.0790 | 0.9273 | 0.9546 | 0.9408 | 0.9780 |
93
+ | 0.0412 | 1.0458 | 640 | 0.0770 | 0.9312 | 0.9515 | 0.9413 | 0.9796 |
94
+ | 0.0535 | 1.0784 | 660 | 0.0868 | 0.9383 | 0.9519 | 0.9450 | 0.9788 |
95
+ | 0.0633 | 1.1111 | 680 | 0.0825 | 0.9239 | 0.9592 | 0.9412 | 0.9788 |
96
+ | 0.0495 | 1.1438 | 700 | 0.0869 | 0.9263 | 0.9615 | 0.9436 | 0.9790 |
97
+ | 0.0612 | 1.1765 | 720 | 0.0729 | 0.9409 | 0.9586 | 0.9497 | 0.9816 |
98
+ | 0.0483 | 1.2092 | 740 | 0.0890 | 0.9218 | 0.9472 | 0.9344 | 0.9777 |
99
+ | 0.0749 | 1.2418 | 760 | 0.0765 | 0.9375 | 0.9538 | 0.9456 | 0.9802 |
100
+ | 0.0732 | 1.2745 | 780 | 0.0824 | 0.9169 | 0.9434 | 0.9300 | 0.9768 |
101
+ | 0.0614 | 1.3072 | 800 | 0.0773 | 0.9381 | 0.9562 | 0.9471 | 0.9799 |
102
+ | 0.0598 | 1.3399 | 820 | 0.0796 | 0.9307 | 0.9599 | 0.9451 | 0.9800 |
103
+ | 0.0608 | 1.3725 | 840 | 0.0810 | 0.9315 | 0.9466 | 0.9390 | 0.9778 |
104
+ | 0.0594 | 1.4052 | 860 | 0.0738 | 0.9367 | 0.9577 | 0.9471 | 0.9801 |
105
+ | 0.0575 | 1.4379 | 880 | 0.0784 | 0.9441 | 0.9504 | 0.9473 | 0.9802 |
106
+ | 0.0616 | 1.4706 | 900 | 0.0853 | 0.9243 | 0.9563 | 0.9401 | 0.9771 |
107
+ | 0.042 | 1.5033 | 920 | 0.0824 | 0.9266 | 0.9442 | 0.9353 | 0.9767 |
108
+ | 0.044 | 1.5359 | 940 | 0.0813 | 0.9263 | 0.9570 | 0.9414 | 0.9789 |
109
+ | 0.0629 | 1.5686 | 960 | 0.0828 | 0.9307 | 0.9601 | 0.9452 | 0.9784 |
110
+ | 0.0502 | 1.6013 | 980 | 0.0743 | 0.9393 | 0.9521 | 0.9457 | 0.9804 |
111
+ | 0.0488 | 1.6340 | 1000 | 0.0849 | 0.9257 | 0.9568 | 0.9410 | 0.9783 |
112
+ | 0.0391 | 1.6667 | 1020 | 0.0779 | 0.9386 | 0.9570 | 0.9477 | 0.9799 |
113
+ | 0.0488 | 1.6993 | 1040 | 0.0787 | 0.9318 | 0.9611 | 0.9462 | 0.9799 |
114
+ | 0.0461 | 1.7320 | 1060 | 0.0807 | 0.9304 | 0.9600 | 0.9450 | 0.9792 |
115
+ | 0.0546 | 1.7647 | 1080 | 0.0761 | 0.9303 | 0.9502 | 0.9401 | 0.9796 |
116
+ | 0.0507 | 1.7974 | 1100 | 0.0747 | 0.9365 | 0.9549 | 0.9456 | 0.9802 |
117
+ | 0.0583 | 1.8301 | 1120 | 0.0706 | 0.9394 | 0.9566 | 0.9479 | 0.9806 |
118
+ | 0.0546 | 1.8627 | 1140 | 0.0736 | 0.9373 | 0.9539 | 0.9455 | 0.9810 |
119
+ | 0.0581 | 1.8954 | 1160 | 0.0829 | 0.9176 | 0.9531 | 0.9350 | 0.9775 |
120
+ | 0.0541 | 1.9281 | 1180 | 0.0792 | 0.9410 | 0.9577 | 0.9493 | 0.9814 |
121
+ | 0.0552 | 1.9608 | 1200 | 0.0807 | 0.9368 | 0.9562 | 0.9464 | 0.9808 |
122
+ | 0.0536 | 1.9935 | 1220 | 0.0759 | 0.9324 | 0.9580 | 0.9450 | 0.9805 |
123
+ | 0.036 | 2.0261 | 1240 | 0.0768 | 0.9338 | 0.9587 | 0.9461 | 0.9806 |
124
+ | 0.0337 | 2.0588 | 1260 | 0.0749 | 0.9367 | 0.9530 | 0.9448 | 0.9807 |
125
+ | 0.0302 | 2.0915 | 1280 | 0.0759 | 0.9380 | 0.9556 | 0.9467 | 0.9805 |
126
+ | 0.0241 | 2.1242 | 1300 | 0.0746 | 0.9376 | 0.9609 | 0.9491 | 0.9819 |
127
+ | 0.0326 | 2.1569 | 1320 | 0.0780 | 0.9317 | 0.9550 | 0.9432 | 0.9803 |
128
+ | 0.0586 | 2.1895 | 1340 | 0.0808 | 0.9251 | 0.9489 | 0.9368 | 0.9785 |
129
+ | 0.0357 | 2.2222 | 1360 | 0.0775 | 0.9333 | 0.9561 | 0.9445 | 0.9801 |
130
+ | 0.0302 | 2.2549 | 1380 | 0.0797 | 0.9345 | 0.9543 | 0.9443 | 0.9801 |
131
+ | 0.0361 | 2.2876 | 1400 | 0.0819 | 0.9344 | 0.9550 | 0.9446 | 0.9796 |
132
+ | 0.0324 | 2.3203 | 1420 | 0.0804 | 0.9363 | 0.9557 | 0.9459 | 0.9802 |
133
+ | 0.0302 | 2.3529 | 1440 | 0.0775 | 0.9400 | 0.9548 | 0.9473 | 0.9812 |
134
+ | 0.0359 | 2.3856 | 1460 | 0.0792 | 0.9363 | 0.9567 | 0.9464 | 0.9805 |
135
+ | 0.0371 | 2.4183 | 1480 | 0.0750 | 0.9399 | 0.9525 | 0.9461 | 0.9810 |
136
+ | 0.0449 | 2.4510 | 1500 | 0.0771 | 0.9300 | 0.9513 | 0.9405 | 0.9796 |
137
+ | 0.0444 | 2.4837 | 1520 | 0.0758 | 0.9306 | 0.9544 | 0.9423 | 0.9795 |
138
+ | 0.037 | 2.5163 | 1540 | 0.0773 | 0.9355 | 0.9576 | 0.9464 | 0.9808 |
139
+ | 0.0372 | 2.5490 | 1560 | 0.0758 | 0.9348 | 0.9591 | 0.9468 | 0.9811 |
140
+ | 0.0403 | 2.5817 | 1580 | 0.0777 | 0.9309 | 0.9585 | 0.9445 | 0.9803 |
141
+ | 0.0401 | 2.6144 | 1600 | 0.0749 | 0.9381 | 0.9593 | 0.9486 | 0.9812 |
142
+ | 0.032 | 2.6471 | 1620 | 0.0751 | 0.9397 | 0.9581 | 0.9488 | 0.9810 |
143
+ | 0.0319 | 2.6797 | 1640 | 0.0768 | 0.9369 | 0.9582 | 0.9475 | 0.9804 |
144
+ | 0.0329 | 2.7124 | 1660 | 0.0752 | 0.9377 | 0.9586 | 0.9480 | 0.9806 |
145
+ | 0.0376 | 2.7451 | 1680 | 0.0748 | 0.9350 | 0.9551 | 0.9449 | 0.9803 |
146
+ | 0.0277 | 2.7778 | 1700 | 0.0761 | 0.9328 | 0.9563 | 0.9444 | 0.9800 |
147
+ | 0.0388 | 2.8105 | 1720 | 0.0771 | 0.9318 | 0.9573 | 0.9444 | 0.9799 |
148
+ | 0.0364 | 2.8431 | 1740 | 0.0759 | 0.9347 | 0.9583 | 0.9464 | 0.9805 |
149
+ | 0.0218 | 2.8758 | 1760 | 0.0755 | 0.9361 | 0.9574 | 0.9466 | 0.9806 |
150
+ | 0.0321 | 2.9085 | 1780 | 0.0750 | 0.9379 | 0.9567 | 0.9472 | 0.9808 |
151
+ | 0.0414 | 2.9412 | 1800 | 0.0742 | 0.9393 | 0.9561 | 0.9476 | 0.9810 |
152
+ | 0.031 | 2.9739 | 1820 | 0.0742 | 0.9394 | 0.9563 | 0.9478 | 0.9810 |
153
 
154
 
155
  ### Framework versions