Hugging Face's logo

apwic
/
nerui-seq_bn-1

TensorBoard
Indonesian
Generated from Trainer
Model card Files Metrics Community
apwic commited on
Commit
40c4276
•
1 Parent(s): d9872e3

Model save

Browse files
Files changed (6) hide show
  1. README.md +172 -0
  2. adapter-ner/adapter_config.json +42 -0
  3. adapter-ner/head_config.json +19 -0
  4. adapter-ner/pytorch_adapter.bin +3 -0
  5. adapter-ner/pytorch_model_head.bin +3 -0
  6. runs/Jun09_14-11-44_a358b85c7679/events.out.tfevents.1717942312.a358b85c7679.52384.0 +2 -2
README.md ADDED
@@ -0,0 +1,172 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ base_model: indolem/indobert-base-uncased
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: nerui-seq_bn-1
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # nerui-seq_bn-1
15
+
16
+ This model is a fine-tuned version of [indolem/indobert-base-uncased](https://huggingface.co/indolem/indobert-base-uncased) on an unknown dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 0.0410
19
+ - Location Precision: 0.9417
20
+ - Location Recall: 0.9741
21
+ - Location F1: 0.9576
22
+ - Location Number: 116
23
+ - Organization Precision: 0.9548
24
+ - Organization Recall: 0.9367
25
+ - Organization F1: 0.9457
26
+ - Organization Number: 158
27
+ - Person Precision: 0.9762
28
+ - Person Recall: 0.9919
29
+ - Person F1: 0.9840
30
+ - Person Number: 124
31
+ - Overall Precision: 0.9576
32
+ - Overall Recall: 0.9648
33
+ - Overall F1: 0.9612
34
+ - Overall Accuracy: 0.9896
35
+
36
+ ## Model description
37
+
38
+ More information needed
39
+
40
+ ## Intended uses & limitations
41
+
42
+ More information needed
43
+
44
+ ## Training and evaluation data
45
+
46
+ More information needed
47
+
48
+ ## Training procedure
49
+
50
+ ### Training hyperparameters
51
+
52
+ The following hyperparameters were used during training:
53
+ - learning_rate: 5e-05
54
+ - train_batch_size: 16
55
+ - eval_batch_size: 64
56
+ - seed: 42
57
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
58
+ - lr_scheduler_type: linear
59
+ - num_epochs: 100.0
60
+
61
+ ### Training results
62
+
63
+ | Training Loss | Epoch | Step | Validation Loss | Location Precision | Location Recall | Location F1 | Location Number | Organization Precision | Organization Recall | Organization F1 | Organization Number | Person Precision | Person Recall | Person F1 | Person Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
64
+ |:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:-------------:|:---------:|:-------------:|:-----------------:|:--------------:|:----------:|:----------------:|
65
+ | 0.8476 | 1.0 | 96 | 0.5342 | 0.0 | 0.0 | 0.0 | 116 | 0.0 | 0.0 | 0.0 | 158 | 0.0 | 0.0 | 0.0 | 124 | 0.0 | 0.0 | 0.0 | 0.8394 |
66
+ | 0.4619 | 2.0 | 192 | 0.3106 | 0.4107 | 0.1983 | 0.2674 | 116 | 0.3641 | 0.4494 | 0.4023 | 158 | 0.3202 | 0.5242 | 0.3976 | 124 | 0.3502 | 0.3995 | 0.3732 | 0.8998 |
67
+ | 0.309 | 3.0 | 288 | 0.2281 | 0.4298 | 0.4224 | 0.4261 | 116 | 0.5021 | 0.7468 | 0.6005 | 158 | 0.5952 | 0.8065 | 0.6849 | 124 | 0.5164 | 0.6709 | 0.5836 | 0.9385 |
68
+ | 0.2191 | 4.0 | 384 | 0.1372 | 0.5969 | 0.6638 | 0.6286 | 116 | 0.6848 | 0.7975 | 0.7368 | 158 | 0.8369 | 0.9516 | 0.8906 | 124 | 0.7070 | 0.8065 | 0.7535 | 0.9624 |
69
+ | 0.1534 | 5.0 | 480 | 0.0976 | 0.752 | 0.8103 | 0.7801 | 116 | 0.7706 | 0.8291 | 0.7988 | 158 | 0.9104 | 0.9839 | 0.9457 | 124 | 0.8089 | 0.8719 | 0.8392 | 0.9728 |
70
+ | 0.1245 | 6.0 | 576 | 0.0794 | 0.8175 | 0.8879 | 0.8512 | 116 | 0.7917 | 0.8418 | 0.8160 | 158 | 0.9318 | 0.9919 | 0.9609 | 124 | 0.8427 | 0.9020 | 0.8714 | 0.9764 |
71
+ | 0.1074 | 7.0 | 672 | 0.0701 | 0.832 | 0.8966 | 0.8631 | 116 | 0.8405 | 0.8671 | 0.8536 | 158 | 0.9535 | 0.9919 | 0.9723 | 124 | 0.8729 | 0.9146 | 0.8933 | 0.9800 |
72
+ | 0.0956 | 8.0 | 768 | 0.0613 | 0.8413 | 0.9138 | 0.8760 | 116 | 0.8580 | 0.8797 | 0.8688 | 158 | 0.9609 | 0.9919 | 0.9762 | 124 | 0.8846 | 0.9246 | 0.9042 | 0.9819 |
73
+ | 0.0854 | 9.0 | 864 | 0.0615 | 0.864 | 0.9310 | 0.8963 | 116 | 0.8161 | 0.8987 | 0.8554 | 158 | 0.9535 | 0.9919 | 0.9723 | 124 | 0.8715 | 0.9372 | 0.9031 | 0.9802 |
74
+ | 0.0781 | 10.0 | 960 | 0.0559 | 0.8770 | 0.9224 | 0.8992 | 116 | 0.8494 | 0.8924 | 0.8704 | 158 | 0.9535 | 0.9919 | 0.9723 | 124 | 0.8897 | 0.9322 | 0.9104 | 0.9819 |
75
+ | 0.0773 | 11.0 | 1056 | 0.0502 | 0.872 | 0.9397 | 0.9046 | 116 | 0.8773 | 0.9051 | 0.8910 | 158 | 0.9609 | 0.9919 | 0.9762 | 124 | 0.9014 | 0.9422 | 0.9214 | 0.9838 |
76
+ | 0.0701 | 12.0 | 1152 | 0.0493 | 0.9008 | 0.9397 | 0.9198 | 116 | 0.8896 | 0.9177 | 0.9034 | 158 | 0.9531 | 0.9839 | 0.9683 | 124 | 0.9126 | 0.9447 | 0.9284 | 0.9846 |
77
+ | 0.0653 | 13.0 | 1248 | 0.0436 | 0.9316 | 0.9397 | 0.9356 | 116 | 0.9177 | 0.9177 | 0.9177 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9378 | 0.9472 | 0.9425 | 0.9863 |
78
+ | 0.0636 | 14.0 | 1344 | 0.0463 | 0.888 | 0.9569 | 0.9212 | 116 | 0.8968 | 0.8797 | 0.8882 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9165 | 0.9372 | 0.9267 | 0.9838 |
79
+ | 0.0611 | 15.0 | 1440 | 0.0423 | 0.9160 | 0.9397 | 0.9277 | 116 | 0.9125 | 0.9241 | 0.9182 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9310 | 0.9497 | 0.9403 | 0.9868 |
80
+ | 0.0613 | 16.0 | 1536 | 0.0437 | 0.9032 | 0.9655 | 0.9333 | 116 | 0.8639 | 0.9241 | 0.8930 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9093 | 0.9573 | 0.9327 | 0.9857 |
81
+ | 0.0625 | 17.0 | 1632 | 0.0420 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9241 | 0.9241 | 0.9241 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9407 | 0.9573 | 0.9489 | 0.9874 |
82
+ | 0.0532 | 18.0 | 1728 | 0.0368 | 0.9322 | 0.9483 | 0.9402 | 116 | 0.9074 | 0.9304 | 0.9187 | 158 | 0.984 | 0.9919 | 0.9880 | 124 | 0.9383 | 0.9548 | 0.9465 | 0.9879 |
83
+ | 0.0501 | 19.0 | 1824 | 0.0369 | 0.9652 | 0.9569 | 0.9610 | 116 | 0.9130 | 0.9304 | 0.9216 | 158 | 0.984 | 0.9919 | 0.9880 | 124 | 0.9501 | 0.9573 | 0.9537 | 0.9890 |
84
+ | 0.047 | 20.0 | 1920 | 0.0409 | 0.8943 | 0.9483 | 0.9205 | 116 | 0.8810 | 0.9367 | 0.9080 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9115 | 0.9573 | 0.9338 | 0.9855 |
85
+ | 0.0464 | 21.0 | 2016 | 0.0365 | 0.8943 | 0.9483 | 0.9205 | 116 | 0.9062 | 0.9177 | 0.9119 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9242 | 0.9497 | 0.9368 | 0.9865 |
86
+ | 0.045 | 22.0 | 2112 | 0.0363 | 0.9328 | 0.9569 | 0.9447 | 116 | 0.8862 | 0.9367 | 0.9108 | 158 | 0.984 | 0.9919 | 0.9880 | 124 | 0.9294 | 0.9598 | 0.9444 | 0.9876 |
87
+ | 0.0416 | 23.0 | 2208 | 0.0357 | 0.9256 | 0.9655 | 0.9451 | 116 | 0.9182 | 0.9241 | 0.9211 | 158 | 0.984 | 0.9919 | 0.9880 | 124 | 0.9407 | 0.9573 | 0.9489 | 0.9887 |
88
+ | 0.042 | 24.0 | 2304 | 0.0373 | 0.925 | 0.9569 | 0.9407 | 116 | 0.9231 | 0.9114 | 0.9172 | 158 | 0.984 | 0.9919 | 0.9880 | 124 | 0.9426 | 0.9497 | 0.9462 | 0.9876 |
89
+ | 0.0394 | 25.0 | 2400 | 0.0363 | 0.9328 | 0.9569 | 0.9447 | 116 | 0.9313 | 0.9430 | 0.9371 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9433 | 0.9623 | 0.9527 | 0.9885 |
90
+ | 0.0362 | 26.0 | 2496 | 0.0338 | 0.9573 | 0.9655 | 0.9614 | 116 | 0.9259 | 0.9494 | 0.9375 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9506 | 0.9673 | 0.9589 | 0.9898 |
91
+ | 0.0379 | 27.0 | 2592 | 0.0337 | 0.9573 | 0.9655 | 0.9614 | 116 | 0.9085 | 0.9430 | 0.9255 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9435 | 0.9648 | 0.9540 | 0.9890 |
92
+ | 0.0328 | 28.0 | 2688 | 0.0362 | 0.9316 | 0.9397 | 0.9356 | 116 | 0.8869 | 0.9430 | 0.9141 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9248 | 0.9573 | 0.9407 | 0.9865 |
93
+ | 0.0347 | 29.0 | 2784 | 0.0354 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.8982 | 0.9494 | 0.9231 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9345 | 0.9673 | 0.9506 | 0.9876 |
94
+ | 0.0314 | 30.0 | 2880 | 0.0360 | 0.9483 | 0.9483 | 0.9483 | 116 | 0.8922 | 0.9430 | 0.9169 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9340 | 0.9598 | 0.9467 | 0.9874 |
95
+ | 0.0312 | 31.0 | 2976 | 0.0323 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9193 | 0.9367 | 0.9279 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9410 | 0.9623 | 0.9516 | 0.9879 |
96
+ | 0.0295 | 32.0 | 3072 | 0.0314 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9554 | 0.9494 | 0.9524 | 158 | 0.984 | 0.9919 | 0.9880 | 124 | 0.9601 | 0.9673 | 0.9637 | 0.9907 |
97
+ | 0.0276 | 33.0 | 3168 | 0.0348 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9308 | 0.9367 | 0.9338 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9504 | 0.9623 | 0.9563 | 0.9893 |
98
+ | 0.0291 | 34.0 | 3264 | 0.0333 | 0.9339 | 0.9741 | 0.9536 | 116 | 0.9430 | 0.9430 | 0.9430 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9506 | 0.9673 | 0.9589 | 0.9904 |
99
+ | 0.0271 | 35.0 | 3360 | 0.0335 | 0.9402 | 0.9483 | 0.9442 | 116 | 0.9371 | 0.9430 | 0.9401 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9502 | 0.9598 | 0.9550 | 0.9898 |
100
+ | 0.0256 | 36.0 | 3456 | 0.0360 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9313 | 0.9430 | 0.9371 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9483 | 0.9673 | 0.9577 | 0.9896 |
101
+ | 0.0251 | 37.0 | 3552 | 0.0347 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9551 | 0.9430 | 0.9490 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9577 | 0.9673 | 0.9625 | 0.9901 |
102
+ | 0.0253 | 38.0 | 3648 | 0.0353 | 0.9328 | 0.9569 | 0.9447 | 116 | 0.9367 | 0.9367 | 0.9367 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9479 | 0.9598 | 0.9538 | 0.9887 |
103
+ | 0.0248 | 39.0 | 3744 | 0.0338 | 0.9167 | 0.9483 | 0.9322 | 116 | 0.9313 | 0.9430 | 0.9371 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9386 | 0.9598 | 0.9491 | 0.9893 |
104
+ | 0.0222 | 40.0 | 3840 | 0.0334 | 0.9407 | 0.9569 | 0.9487 | 116 | 0.9437 | 0.9557 | 0.9497 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9530 | 0.9673 | 0.9601 | 0.9896 |
105
+ | 0.0226 | 41.0 | 3936 | 0.0345 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9255 | 0.9430 | 0.9342 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9481 | 0.9648 | 0.9564 | 0.9898 |
106
+ | 0.0208 | 42.0 | 4032 | 0.0345 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9551 | 0.9430 | 0.9490 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9898 |
107
+ | 0.0227 | 43.0 | 4128 | 0.0355 | 0.9483 | 0.9483 | 0.9483 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9573 | 0.9573 | 0.9573 | 0.9887 |
108
+ | 0.0222 | 44.0 | 4224 | 0.0370 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9367 | 0.9367 | 0.9367 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9504 | 0.9623 | 0.9563 | 0.9893 |
109
+ | 0.0197 | 45.0 | 4320 | 0.0362 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9574 | 0.9598 | 0.9586 | 0.9896 |
110
+ | 0.0189 | 46.0 | 4416 | 0.0375 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9308 | 0.9367 | 0.9338 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9457 | 0.9623 | 0.9539 | 0.9890 |
111
+ | 0.02 | 47.0 | 4512 | 0.0363 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9255 | 0.9430 | 0.9342 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9458 | 0.9648 | 0.9552 | 0.9893 |
112
+ | 0.0178 | 48.0 | 4608 | 0.0369 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9599 | 0.9623 | 0.9611 | 0.9893 |
113
+ | 0.02 | 49.0 | 4704 | 0.0357 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9575 | 0.9623 | 0.9599 | 0.9896 |
114
+ | 0.0178 | 50.0 | 4800 | 0.0368 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9673 | 0.9367 | 0.9518 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9647 | 0.9623 | 0.9635 | 0.9893 |
115
+ | 0.0192 | 51.0 | 4896 | 0.0337 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9430 | 0.9430 | 0.9430 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9529 | 0.9648 | 0.9588 | 0.9898 |
116
+ | 0.0173 | 52.0 | 4992 | 0.0352 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9615 | 0.9494 | 0.9554 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9625 | 0.9673 | 0.9649 | 0.9904 |
117
+ | 0.0169 | 53.0 | 5088 | 0.0353 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9434 | 0.9494 | 0.9464 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9553 | 0.9673 | 0.9613 | 0.9890 |
118
+ | 0.0153 | 54.0 | 5184 | 0.0351 | 0.9573 | 0.9655 | 0.9614 | 116 | 0.9618 | 0.9557 | 0.9587 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.965 | 0.9698 | 0.9674 | 0.9898 |
119
+ | 0.0145 | 55.0 | 5280 | 0.0349 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9613 | 0.9430 | 0.9521 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9624 | 0.9648 | 0.9636 | 0.9898 |
120
+ | 0.0155 | 56.0 | 5376 | 0.0360 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9490 | 0.9430 | 0.9460 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9553 | 0.9673 | 0.9613 | 0.9901 |
121
+ | 0.016 | 57.0 | 5472 | 0.0376 | 0.9573 | 0.9655 | 0.9614 | 116 | 0.9613 | 0.9430 | 0.9521 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9648 | 0.9648 | 0.9648 | 0.9898 |
122
+ | 0.0143 | 58.0 | 5568 | 0.0389 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9671 | 0.9304 | 0.9484 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9622 | 0.9598 | 0.9610 | 0.9893 |
123
+ | 0.0156 | 59.0 | 5664 | 0.0370 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9427 | 0.9367 | 0.9397 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9504 | 0.9623 | 0.9563 | 0.9901 |
124
+ | 0.0152 | 60.0 | 5760 | 0.0367 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9574 | 0.9598 | 0.9586 | 0.9896 |
125
+ | 0.0144 | 61.0 | 5856 | 0.0407 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.955 | 0.9598 | 0.9574 | 0.9893 |
126
+ | 0.0127 | 62.0 | 5952 | 0.0389 | 0.9407 | 0.9569 | 0.9487 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9573 | 0.9573 | 0.9573 | 0.9890 |
127
+ | 0.0149 | 63.0 | 6048 | 0.0402 | 0.9328 | 0.9569 | 0.9447 | 116 | 0.9304 | 0.9304 | 0.9304 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9454 | 0.9573 | 0.9513 | 0.9879 |
128
+ | 0.0119 | 64.0 | 6144 | 0.0412 | 0.9316 | 0.9397 | 0.9356 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9685 | 0.9919 | 0.9801 | 124 | 0.9523 | 0.9523 | 0.9523 | 0.9887 |
129
+ | 0.0117 | 65.0 | 6240 | 0.0380 | 0.9407 | 0.9569 | 0.9487 | 116 | 0.9542 | 0.9241 | 0.9389 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9572 | 0.9548 | 0.9560 | 0.9887 |
130
+ | 0.013 | 66.0 | 6336 | 0.0384 | 0.9402 | 0.9483 | 0.9442 | 116 | 0.9542 | 0.9241 | 0.9389 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9571 | 0.9523 | 0.9547 | 0.9885 |
131
+ | 0.012 | 67.0 | 6432 | 0.0413 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9735 | 0.9304 | 0.9515 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9671 | 0.9598 | 0.9634 | 0.9893 |
132
+ | 0.0112 | 68.0 | 6528 | 0.0399 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9599 | 0.9623 | 0.9611 | 0.9896 |
133
+ | 0.0129 | 69.0 | 6624 | 0.0367 | 0.9652 | 0.9569 | 0.9610 | 116 | 0.9490 | 0.9430 | 0.9460 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9623 | 0.9623 | 0.9623 | 0.9898 |
134
+ | 0.0115 | 70.0 | 6720 | 0.0381 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9427 | 0.9367 | 0.9397 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9504 | 0.9623 | 0.9563 | 0.9890 |
135
+ | 0.0119 | 71.0 | 6816 | 0.0381 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9608 | 0.9304 | 0.9453 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9598 | 0.9598 | 0.9598 | 0.9890 |
136
+ | 0.0127 | 72.0 | 6912 | 0.0418 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9598 | 0.9598 | 0.9598 | 0.9890 |
137
+ | 0.011 | 73.0 | 7008 | 0.0408 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9551 | 0.9623 | 0.9587 | 0.9890 |
138
+ | 0.0121 | 74.0 | 7104 | 0.0426 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.955 | 0.9598 | 0.9574 | 0.9890 |
139
+ | 0.0122 | 75.0 | 7200 | 0.0391 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9484 | 0.9304 | 0.9393 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.955 | 0.9598 | 0.9574 | 0.9893 |
140
+ | 0.0108 | 76.0 | 7296 | 0.0401 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9551 | 0.9623 | 0.9587 | 0.9890 |
141
+ | 0.0103 | 77.0 | 7392 | 0.0402 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9574 | 0.9598 | 0.9586 | 0.9887 |
142
+ | 0.0105 | 78.0 | 7488 | 0.0404 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9896 |
143
+ | 0.0106 | 79.0 | 7584 | 0.0419 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9671 | 0.9304 | 0.9484 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9623 | 0.9623 | 0.9623 | 0.9896 |
144
+ | 0.0111 | 80.0 | 7680 | 0.0401 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9490 | 0.9430 | 0.9460 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9893 |
145
+ | 0.0109 | 81.0 | 7776 | 0.0395 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9313 | 0.9430 | 0.9371 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9505 | 0.9648 | 0.9576 | 0.9896 |
146
+ | 0.0093 | 82.0 | 7872 | 0.0401 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9527 | 0.9623 | 0.9575 | 0.9898 |
147
+ | 0.0097 | 83.0 | 7968 | 0.0397 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9430 | 0.9430 | 0.9430 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9529 | 0.9648 | 0.9588 | 0.9901 |
148
+ | 0.0099 | 84.0 | 8064 | 0.0411 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9552 | 0.9648 | 0.96 | 0.9898 |
149
+ | 0.0109 | 85.0 | 8160 | 0.0399 | 0.9492 | 0.9655 | 0.9573 | 116 | 0.9371 | 0.9430 | 0.9401 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9529 | 0.9648 | 0.9588 | 0.9898 |
150
+ | 0.0086 | 86.0 | 8256 | 0.0415 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9484 | 0.9304 | 0.9393 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9526 | 0.9598 | 0.9562 | 0.9890 |
151
+ | 0.0099 | 87.0 | 8352 | 0.0413 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9308 | 0.9367 | 0.9338 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9457 | 0.9623 | 0.9539 | 0.9896 |
152
+ | 0.0096 | 88.0 | 8448 | 0.0412 | 0.9487 | 0.9569 | 0.9528 | 116 | 0.925 | 0.9367 | 0.9308 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9479 | 0.9598 | 0.9538 | 0.9893 |
153
+ | 0.0092 | 89.0 | 8544 | 0.0424 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9896 |
154
+ | 0.0095 | 90.0 | 8640 | 0.0422 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9484 | 0.9304 | 0.9393 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.955 | 0.9598 | 0.9574 | 0.9893 |
155
+ | 0.0097 | 91.0 | 8736 | 0.0420 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9608 | 0.9304 | 0.9453 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9574 | 0.9598 | 0.9586 | 0.9893 |
156
+ | 0.0089 | 92.0 | 8832 | 0.0410 | 0.9407 | 0.9569 | 0.9487 | 116 | 0.9423 | 0.9304 | 0.9363 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9525 | 0.9573 | 0.9549 | 0.9887 |
157
+ | 0.009 | 93.0 | 8928 | 0.0400 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9527 | 0.9623 | 0.9575 | 0.9893 |
158
+ | 0.0087 | 94.0 | 9024 | 0.0399 | 0.9407 | 0.9569 | 0.9487 | 116 | 0.9363 | 0.9304 | 0.9333 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9501 | 0.9573 | 0.9537 | 0.9890 |
159
+ | 0.0104 | 95.0 | 9120 | 0.0406 | 0.9333 | 0.9655 | 0.9492 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9527 | 0.9623 | 0.9575 | 0.9893 |
160
+ | 0.0096 | 96.0 | 9216 | 0.0407 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9896 |
161
+ | 0.009 | 97.0 | 9312 | 0.0406 | 0.9412 | 0.9655 | 0.9532 | 116 | 0.9487 | 0.9367 | 0.9427 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9551 | 0.9623 | 0.9587 | 0.9890 |
162
+ | 0.0077 | 98.0 | 9408 | 0.0411 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9896 |
163
+ | 0.0089 | 99.0 | 9504 | 0.0410 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9545 | 0.9304 | 0.9423 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9575 | 0.9623 | 0.9599 | 0.9893 |
164
+ | 0.0088 | 100.0 | 9600 | 0.0410 | 0.9417 | 0.9741 | 0.9576 | 116 | 0.9548 | 0.9367 | 0.9457 | 158 | 0.9762 | 0.9919 | 0.9840 | 124 | 0.9576 | 0.9648 | 0.9612 | 0.9896 |
165
+
166
+
167
+ ### Framework versions
168
+
169
+ - Transformers 4.39.3
170
+ - Pytorch 2.3.0+cu121
171
+ - Datasets 2.19.1
172
+ - Tokenizers 0.15.2
adapter-ner/adapter_config.json ADDED
@@ -0,0 +1,42 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": {
3
+ "adapter_residual_before_ln": false,
4
+ "cross_adapter": false,
5
+ "dropout": 0.0,
6
+ "factorized_phm_W": true,
7
+ "factorized_phm_rule": false,
8
+ "hypercomplex_nonlinearity": "glorot-uniform",
9
+ "init_weights": "bert",
10
+ "inv_adapter": null,
11
+ "inv_adapter_reduction_factor": null,
12
+ "is_parallel": false,
13
+ "learn_phm": true,
14
+ "leave_out": [],
15
+ "ln_after": false,
16
+ "ln_before": false,
17
+ "mh_adapter": false,
18
+ "non_linearity": "relu",
19
+ "original_ln_after": true,
20
+ "original_ln_before": true,
21
+ "output_adapter": true,
22
+ "phm_bias": true,
23
+ "phm_c_init": "normal",
24
+ "phm_dim": 4,
25
+ "phm_init_range": 0.0001,
26
+ "phm_layer": false,
27
+ "phm_rank": 1,
28
+ "reduction_factor": 16,
29
+ "residual_before_ln": true,
30
+ "scaling": 1.0,
31
+ "shared_W_phm": false,
32
+ "shared_phm_rule": true,
33
+ "use_gating": false
34
+ },
35
+ "config_id": "9076f36a74755ac4",
36
+ "hidden_size": 768,
37
+ "model_class": "BertForTokenClassification",
38
+ "model_name": "indolem/indobert-base-uncased",
39
+ "model_type": "bert",
40
+ "name": "adapter-ner",
41
+ "version": "0.2.0"
42
+ }
adapter-ner/head_config.json ADDED
@@ -0,0 +1,19 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "config": null,
3
+ "hidden_size": 768,
4
+ "label2id": {
5
+ "B-LOCATION": 0,
6
+ "B-ORGANIZATION": 1,
7
+ "B-PERSON": 2,
8
+ "I-LOCATION": 3,
9
+ "I-ORGANIZATION": 4,
10
+ "I-PERSON": 5,
11
+ "O": 6
12
+ },
13
+ "model_class": "BertForTokenClassification",
14
+ "model_name": "indolem/indobert-base-uncased",
15
+ "model_type": "bert",
16
+ "name": null,
17
+ "num_labels": 7,
18
+ "version": "0.2.0"
19
+ }
adapter-ner/pytorch_adapter.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fe67efc377513be540f31cf23c31a0fdbe59ad58eba2de51cf9f64b1d4eada6f
3
+ size 3595750
adapter-ner/pytorch_model_head.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a6d8232622af65e3da6096100c56d1939d16d8b8207387a9c14b724bef27edcf
3
+ size 23066
runs/Jun09_14-11-44_a358b85c7679/events.out.tfevents.1717942312.a358b85c7679.52384.0 CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:77216f6cab1bc0b439175327a55ace18bb91f03e50edb72f1ec46cc7a7d3c7a1
3
- size 146341
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c9c7c9543163080cc4f0654cbd967a5442434215e1db7fcf5189930b3d768fad
3
+ size 148123