Hugging Face's logo

csNoHug
/
distilbert-base-uncased-finetuned-ner-cadec-active

Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
csNoHug commited on
Commit
2c6e992
•
1 Parent(s): 68154d5

Training complete

Browse files
Files changed (1) hide show
  1. README.md +35 -35
README.md CHANGED
@@ -20,58 +20,58 @@ should probably proofread and complete it, then remove this comment. -->
20
 
21
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
22
  It achieves the following results on the evaluation set:
23
- - Loss: 0.3991
24
- - Precision: 0.4343
25
- - Recall: 0.3889
26
- - F1: 0.4104
27
- - Accuracy: 0.8844
28
- - Adr Precision: 0.3362
29
- - Adr Recall: 0.3387
30
- - Adr F1: 0.3374
31
  - Disease Precision: 0.0
32
  - Disease Recall: 0.0
33
  - Disease F1: 0.0
34
- - Drug Precision: 0.8077
35
- - Drug Recall: 0.7819
36
- - Drug F1: 0.7946
37
  - Finding Precision: 0.0
38
  - Finding Recall: 0.0
39
  - Finding F1: 0.0
40
  - Symptom Precision: 0.0
41
  - Symptom Recall: 0.0
42
  - Symptom F1: 0.0
43
- - B-adr Precision: 0.6463
44
- - B-adr Recall: 0.3827
45
- - B-adr F1: 0.4807
46
  - B-disease Precision: 0.0
47
  - B-disease Recall: 0.0
48
  - B-disease F1: 0.0
49
- - B-drug Precision: 0.9463
50
- - B-drug Recall: 0.75
51
- - B-drug F1: 0.8368
52
  - B-finding Precision: 0.0
53
  - B-finding Recall: 0.0
54
  - B-finding F1: 0.0
55
  - B-symptom Precision: 0.0
56
  - B-symptom Recall: 0.0
57
  - B-symptom F1: 0.0
58
- - I-adr Precision: 0.2517
59
- - I-adr Recall: 0.2675
60
- - I-adr F1: 0.2594
61
  - I-disease Precision: 0.0
62
  - I-disease Recall: 0.0
63
  - I-disease F1: 0.0
64
- - I-drug Precision: 0.7790
65
- - I-drug Recall: 0.7540
66
- - I-drug F1: 0.7663
67
  - I-finding Precision: 0.0
68
  - I-finding Recall: 0.0
69
  - I-finding F1: 0.0
70
  - I-symptom Precision: 0.0
71
  - I-symptom Recall: 0.0
72
  - I-symptom F1: 0.0
73
- - Macro Avg F1: 0.2343
74
- - Weighted Avg F1: 0.4310
75
 
76
  ## Model description
77
 
@@ -102,16 +102,16 @@ The following hyperparameters were used during training:
102
 
103
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Adr Precision | Adr Recall | Adr F1 | Disease Precision | Disease Recall | Disease F1 | Drug Precision | Drug Recall | Drug F1 | Finding Precision | Finding Recall | Finding F1 | Symptom Precision | Symptom Recall | Symptom F1 | B-adr Precision | B-adr Recall | B-adr F1 | B-disease Precision | B-disease Recall | B-disease F1 | B-drug Precision | B-drug Recall | B-drug F1 | B-finding Precision | B-finding Recall | B-finding F1 | B-symptom Precision | B-symptom Recall | B-symptom F1 | I-adr Precision | I-adr Recall | I-adr F1 | I-disease Precision | I-disease Recall | I-disease F1 | I-drug Precision | I-drug Recall | I-drug F1 | I-finding Precision | I-finding Recall | I-finding F1 | I-symptom Precision | I-symptom Recall | I-symptom F1 | Macro Avg F1 | Weighted Avg F1 |
104
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|:------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------:|:-------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:------------:|:---------------:|
105
- | No log | 1.0 | 16 | 0.8107 | 0.0 | 0.0 | 0.0 | 0.7876 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
106
- | No log | 2.0 | 32 | 0.5639 | 0.2126 | 0.1382 | 0.1675 | 0.8328 | 0.2139 | 0.1962 | 0.2047 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 1.0 | 0.0213 | 0.0417 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0555 | 0.0628 | 0.0589 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0101 | 0.0234 |
107
- | No log | 3.0 | 48 | 0.4822 | 0.4020 | 0.2835 | 0.3325 | 0.8593 | 0.3002 | 0.2456 | 0.2702 | 0.0 | 0.0 | 0.0 | 0.8571 | 0.5745 | 0.6879 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9841 | 0.6596 | 0.7898 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0552 | 0.0557 | 0.0554 | 0.0 | 0.0 | 0.0 | 0.9730 | 0.5775 | 0.7248 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1570 | 0.1809 |
108
- | No log | 4.0 | 64 | 0.4422 | 0.4168 | 0.3255 | 0.3655 | 0.8608 | 0.3084 | 0.2820 | 0.2946 | 0.0 | 0.0 | 0.0 | 0.9254 | 0.6596 | 0.7702 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5 | 0.0047 | 0.0094 | 0.0 | 0.0 | 0.0 | 0.9767 | 0.6702 | 0.7950 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0653 | 0.0736 | 0.0692 | 0.0 | 0.0 | 0.0 | 0.9549 | 0.6791 | 0.7937 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1667 | 0.1967 |
109
- | No log | 5.0 | 80 | 0.4164 | 0.4113 | 0.3347 | 0.3691 | 0.8649 | 0.3130 | 0.2907 | 0.3014 | 0.0 | 0.0 | 0.0 | 0.8141 | 0.6755 | 0.7384 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5833 | 0.0551 | 0.1007 | 0.0 | 0.0 | 0.0 | 0.9699 | 0.6862 | 0.8037 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0905 | 0.1023 | 0.0960 | 0.0 | 0.0 | 0.0 | 0.8903 | 0.7380 | 0.8070 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1808 | 0.2409 |
110
- | No log | 6.0 | 96 | 0.4044 | 0.4079 | 0.3490 | 0.3762 | 0.8746 | 0.3103 | 0.3009 | 0.3055 | 0.0 | 0.0 | 0.0 | 0.7929 | 0.7128 | 0.7507 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6182 | 0.2142 | 0.3181 | 0.0 | 0.0 | 0.0 | 0.9710 | 0.7128 | 0.8221 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1532 | 0.1706 | 0.1614 | 0.0 | 0.0 | 0.0 | 0.8512 | 0.7647 | 0.8056 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2107 | 0.3430 |
111
- | No log | 7.0 | 112 | 0.4013 | 0.4118 | 0.3797 | 0.3951 | 0.8755 | 0.3155 | 0.3256 | 0.3205 | 0.0 | 0.0 | 0.0 | 0.7696 | 0.7819 | 0.7757 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6202 | 0.2803 | 0.3861 | 0.0 | 0.0 | 0.0 | 0.9524 | 0.7447 | 0.8358 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1751 | 0.2047 | 0.1887 | 0.0 | 0.0 | 0.0 | 0.7696 | 0.7861 | 0.7778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2188 | 0.3750 |
112
- | No log | 8.0 | 128 | 0.4008 | 0.4297 | 0.3756 | 0.4009 | 0.8820 | 0.3275 | 0.3241 | 0.3258 | 0.0 | 0.0 | 0.0 | 0.8324 | 0.7660 | 0.7978 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6507 | 0.3433 | 0.4495 | 0.0 | 0.0 | 0.0 | 0.9653 | 0.7394 | 0.8373 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2271 | 0.2406 | 0.2337 | 0.0 | 0.0 | 0.0 | 0.8129 | 0.7433 | 0.7765 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2297 | 0.4125 |
113
- | No log | 9.0 | 144 | 0.3987 | 0.4323 | 0.3920 | 0.4112 | 0.8843 | 0.3348 | 0.3430 | 0.3388 | 0.0 | 0.0 | 0.0 | 0.8122 | 0.7819 | 0.7967 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6380 | 0.3969 | 0.4893 | 0.0 | 0.0 | 0.0 | 0.9658 | 0.75 | 0.8443 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2487 | 0.2639 | 0.2561 | 0.0 | 0.0 | 0.0 | 0.7790 | 0.7540 | 0.7663 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2356 | 0.4339 |
114
- | No log | 10.0 | 160 | 0.3991 | 0.4343 | 0.3889 | 0.4104 | 0.8844 | 0.3362 | 0.3387 | 0.3374 | 0.0 | 0.0 | 0.0 | 0.8077 | 0.7819 | 0.7946 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6463 | 0.3827 | 0.4807 | 0.0 | 0.0 | 0.0 | 0.9463 | 0.75 | 0.8368 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2517 | 0.2675 | 0.2594 | 0.0 | 0.0 | 0.0 | 0.7790 | 0.7540 | 0.7663 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2343 | 0.4310 |
115
 
116
 
117
  ### Framework versions
 
20
 
21
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 0.3797
24
+ - Precision: 0.4683
25
+ - Recall: 0.4688
26
+ - F1: 0.4685
27
+ - Accuracy: 0.8922
28
+ - Adr Precision: 0.3881
29
+ - Adr Recall: 0.4462
30
+ - Adr F1: 0.4151
31
  - Disease Precision: 0.0
32
  - Disease Recall: 0.0
33
  - Disease F1: 0.0
34
+ - Drug Precision: 0.8075
35
+ - Drug Recall: 0.8032
36
+ - Drug F1: 0.8053
37
  - Finding Precision: 0.0
38
  - Finding Recall: 0.0
39
  - Finding F1: 0.0
40
  - Symptom Precision: 0.0
41
  - Symptom Recall: 0.0
42
  - Symptom F1: 0.0
43
+ - B-adr Precision: 0.6058
44
+ - B-adr Recall: 0.5591
45
+ - B-adr F1: 0.5815
46
  - B-disease Precision: 0.0
47
  - B-disease Recall: 0.0
48
  - B-disease F1: 0.0
49
+ - B-drug Precision: 0.9571
50
+ - B-drug Recall: 0.8298
51
+ - B-drug F1: 0.8889
52
  - B-finding Precision: 0.0
53
  - B-finding Recall: 0.0
54
  - B-finding F1: 0.0
55
  - B-symptom Precision: 0.0
56
  - B-symptom Recall: 0.0
57
  - B-symptom F1: 0.0
58
+ - I-adr Precision: 0.3421
59
+ - I-adr Recall: 0.3734
60
+ - I-adr F1: 0.3571
61
  - I-disease Precision: 0.0
62
  - I-disease Recall: 0.0
63
  - I-disease F1: 0.0
64
+ - I-drug Precision: 0.8370
65
+ - I-drug Recall: 0.8235
66
+ - I-drug F1: 0.8302
67
  - I-finding Precision: 0.0
68
  - I-finding Recall: 0.0
69
  - I-finding F1: 0.0
70
  - I-symptom Precision: 0.0
71
  - I-symptom Recall: 0.0
72
  - I-symptom F1: 0.0
73
+ - Macro Avg F1: 0.2658
74
+ - Weighted Avg F1: 0.5115
75
 
76
  ## Model description
77
 
 
102
 
103
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Adr Precision | Adr Recall | Adr F1 | Disease Precision | Disease Recall | Disease F1 | Drug Precision | Drug Recall | Drug F1 | Finding Precision | Finding Recall | Finding F1 | Symptom Precision | Symptom Recall | Symptom F1 | B-adr Precision | B-adr Recall | B-adr F1 | B-disease Precision | B-disease Recall | B-disease F1 | B-drug Precision | B-drug Recall | B-drug F1 | B-finding Precision | B-finding Recall | B-finding F1 | B-symptom Precision | B-symptom Recall | B-symptom F1 | I-adr Precision | I-adr Recall | I-adr F1 | I-disease Precision | I-disease Recall | I-disease F1 | I-drug Precision | I-drug Recall | I-drug F1 | I-finding Precision | I-finding Recall | I-finding F1 | I-symptom Precision | I-symptom Recall | I-symptom F1 | Macro Avg F1 | Weighted Avg F1 |
104
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|:------:|:-----------------:|:--------------:|:----------:|:--------------:|:-----------:|:-------:|:-----------------:|:--------------:|:----------:|:-----------------:|:--------------:|:----------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:---------------:|:------------:|:--------:|:-------------------:|:----------------:|:------------:|:----------------:|:-------------:|:---------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:------------:|:---------------:|
105
+ | No log | 1.0 | 19 | 0.8069 | 0.0 | 0.0 | 0.0 | 0.7876 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
106
+ | No log | 2.0 | 38 | 0.5346 | 0.3171 | 0.1668 | 0.2186 | 0.8475 | 0.2268 | 0.1279 | 0.1636 | 0.0 | 0.0 | 0.0 | 0.5952 | 0.3989 | 0.4777 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.9841 | 0.6596 | 0.7898 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0747 | 0.0521 | 0.0614 | 0.0 | 0.0 | 0.0 | 0.9615 | 0.4011 | 0.5660 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1417 | 0.1657 |
107
+ | No log | 3.0 | 57 | 0.4568 | 0.4028 | 0.2907 | 0.3377 | 0.8619 | 0.2777 | 0.2297 | 0.2514 | 0.0 | 0.0 | 0.0 | 0.9265 | 0.6702 | 0.7778 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5124 | 0.0976 | 0.1640 | 0.0 | 0.0 | 0.0 | 0.9846 | 0.6809 | 0.8050 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1075 | 0.1023 | 0.1049 | 0.0 | 0.0 | 0.0 | 0.9338 | 0.6791 | 0.7864 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1860 | 0.2648 |
108
+ | No log | 4.0 | 76 | 0.4164 | 0.4110 | 0.3286 | 0.3652 | 0.8643 | 0.3018 | 0.2733 | 0.2868 | 0.0 | 0.0 | 0.0 | 0.8418 | 0.7074 | 0.7688 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6184 | 0.0740 | 0.1322 | 0.0 | 0.0 | 0.0 | 0.9662 | 0.7606 | 0.8512 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0855 | 0.0934 | 0.0893 | 0.0 | 0.0 | 0.0 | 0.8590 | 0.7166 | 0.7813 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1854 | 0.2526 |
109
+ | No log | 5.0 | 95 | 0.3960 | 0.4371 | 0.3838 | 0.4087 | 0.8776 | 0.3417 | 0.3358 | 0.3387 | 0.0 | 0.0 | 0.0 | 0.7912 | 0.7660 | 0.7784 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6197 | 0.2772 | 0.3830 | 0.0 | 0.0 | 0.0 | 0.9490 | 0.7926 | 0.8638 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1893 | 0.2029 | 0.1958 | 0.0 | 0.0 | 0.0 | 0.8483 | 0.8075 | 0.8274 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2270 | 0.3845 |
110
+ | No log | 6.0 | 114 | 0.3851 | 0.4465 | 0.4145 | 0.4299 | 0.8859 | 0.3537 | 0.3706 | 0.3620 | 0.0 | 0.0 | 0.0 | 0.8065 | 0.7979 | 0.8021 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6179 | 0.3921 | 0.4798 | 0.0 | 0.0 | 0.0 | 0.9565 | 0.8191 | 0.8825 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2441 | 0.2621 | 0.2528 | 0.0 | 0.0 | 0.0 | 0.8352 | 0.8128 | 0.8238 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2439 | 0.4397 |
111
+ | No log | 7.0 | 133 | 0.3813 | 0.4567 | 0.4483 | 0.4525 | 0.8896 | 0.3697 | 0.4186 | 0.3926 | 0.0 | 0.0 | 0.0 | 0.8333 | 0.7979 | 0.8152 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.5981 | 0.5087 | 0.5498 | 0.0 | 0.0 | 0.0 | 0.9747 | 0.8191 | 0.8902 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3088 | 0.3321 | 0.3201 | 0.0 | 0.0 | 0.0 | 0.8436 | 0.8075 | 0.8251 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2585 | 0.4877 |
112
+ | No log | 8.0 | 152 | 0.3785 | 0.4644 | 0.4534 | 0.4588 | 0.8908 | 0.3817 | 0.4244 | 0.4019 | 0.0 | 0.0 | 0.0 | 0.7989 | 0.8032 | 0.8011 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6143 | 0.4992 | 0.5508 | 0.0 | 0.0 | 0.0 | 0.9512 | 0.8298 | 0.8864 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3245 | 0.3537 | 0.3385 | 0.0 | 0.0 | 0.0 | 0.8432 | 0.8342 | 0.8387 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2614 | 0.4950 |
113
+ | No log | 9.0 | 171 | 0.3795 | 0.4542 | 0.4565 | 0.4553 | 0.8890 | 0.3711 | 0.4288 | 0.3978 | 0.0 | 0.0 | 0.0 | 0.8075 | 0.8032 | 0.8053 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6049 | 0.5496 | 0.5759 | 0.0 | 0.0 | 0.0 | 0.9573 | 0.8351 | 0.8920 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3236 | 0.3573 | 0.3396 | 0.0 | 0.0 | 0.0 | 0.8432 | 0.8342 | 0.8387 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2646 | 0.5051 |
114
+ | No log | 10.0 | 190 | 0.3797 | 0.4683 | 0.4688 | 0.4685 | 0.8922 | 0.3881 | 0.4462 | 0.4151 | 0.0 | 0.0 | 0.0 | 0.8075 | 0.8032 | 0.8053 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.6058 | 0.5591 | 0.5815 | 0.0 | 0.0 | 0.0 | 0.9571 | 0.8298 | 0.8889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3421 | 0.3734 | 0.3571 | 0.0 | 0.0 | 0.0 | 0.8370 | 0.8235 | 0.8302 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2658 | 0.5115 |
115
 
116
 
117
  ### Framework versions