Hugging Face's logo

aishanur
/
HVD_Roberta_Large_Upsampled

Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
Inference Endpoints
Model card Files Community
aishanur commited on
Commit
be7ffa3
•
1 Parent(s): 1b87f00

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +2 -91
README.md CHANGED
@@ -11,88 +11,9 @@ model-index:
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
- # roberta_large_hv_3
15
 
16
- This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the None dataset.
17
- It achieves the following results on the evaluation set:
18
- - Loss: 0.0599
19
- - F1-macro subtask 1: 0.2635
20
- - F1-micro subtask 1: 0.3292
21
- - Roc auc macro subtask 1: 0.6016
22
- - F1-macro subtask 2: 0.0502
23
- - F1-micro subtask 2: 0.0513
24
- - Roc auc macro subtask 2: 0.6128
25
- - Self-direction: thought1: 0.0588
26
- - Self-direction: action1: 0.1801
27
- - Stimulation1: 0.1815
28
- - Hedonism1: 0.2645
29
- - Achievement1: 0.2612
30
- - Power: dominance1: 0.3455
31
- - Power: resources1: 0.2642
32
- - Face1: 0.1941
33
- - Security: personal1: 0.2454
34
- - Security: societal1: 0.4119
35
- - Tradition1: 0.4361
36
- - Conformity: rules1: 0.4578
37
- - Conformity: interpersonal1: 0.0700
38
- - Humility1: 0.0833
39
- - Benevolence: caring1: 0.1117
40
- - Benevolence: dependability1: 0.2426
41
- - Universalism: concern1: 0.3619
42
- - Universalism: nature1: 0.5693
43
- - Universalism: tolerance1: 0.2667
44
- - Self-direction: thought attained2: 0.0190
45
- - Self-direction: thought constrained2: 0.0561
46
- - Self-direction: action attained2: 0.0525
47
- - Self-direction: action constrained2: 0.0762
48
- - Stimulation attained2: 0.0631
49
- - Stimulation constrained2: 0.0095
50
- - Hedonism attained2: 0.0143
51
- - Hedonism constrained2: 0.0071
52
- - Achievement attained2: 0.1248
53
- - Achievement constrained2: 0.0840
54
- - Power: dominance attained2: 0.0701
55
- - Power: dominance constrained2: 0.0767
56
- - Power: resources attained2: 0.0806
57
- - Power: resources constrained2: 0.0807
58
- - Face attained2: 0.0239
59
- - Face constrained2: 0.0361
60
- - Security: personal attained2: 0.0187
61
- - Security: personal constrained2: 0.0425
62
- - Security: societal attained2: 0.1038
63
- - Security: societal constrained2: 0.1802
64
- - Tradition attained2: 0.0312
65
- - Tradition constrained2: 0.0338
66
- - Conformity: rules attained2: 0.1044
67
- - Conformity: rules constrained2: 0.0914
68
- - Conformity: interpersonal attained2: 0.0162
69
- - Conformity: interpersonal constrained2: 0.0294
70
- - Humility attained2: 0.0053
71
- - Humility constrained2: 0.0024
72
- - Benevolence: caring attained2: 0.0438
73
- - Benevolence: caring constrained2: 0.0137
74
- - Benevolence: dependability attained2: 0.0362
75
- - Benevolence: dependability constrained2: 0.016
76
- - Universalism: concern attained2: 0.0852
77
- - Universalism: concern constrained2: 0.0583
78
- - Universalism: nature attained2: 0.0423
79
- - Universalism: nature constrained2: 0.0516
80
- - Universalism: tolerance attained2: 0.0142
81
- - Universalism: tolerance constrained2: 0.0133
82
-
83
- ## Model description
84
-
85
- More information needed
86
-
87
- ## Intended uses & limitations
88
-
89
- More information needed
90
-
91
- ## Training and evaluation data
92
-
93
- More information needed
94
-
95
- ## Training procedure
96
 
97
  ### Training hyperparameters
98
 
@@ -106,16 +27,6 @@ The following hyperparameters were used during training:
106
  - lr_scheduler_warmup_ratio: 0.2
107
  - num_epochs: 4
108
 
109
- ### Training results
110
-
111
- | Training Loss | Epoch | Step | Validation Loss | F1-macro subtask 1 | F1-micro subtask 1 | Roc auc macro subtask 1 | F1-macro subtask 2 | F1-micro subtask 2 | Roc auc macro subtask 2 | Self-direction: thought1 | Self-direction: action1 | Stimulation1 | Hedonism1 | Achievement1 | Power: dominance1 | Power: resources1 | Face1 | Security: personal1 | Security: societal1 | Tradition1 | Conformity: rules1 | Conformity: interpersonal1 | Humility1 | Benevolence: caring1 | Benevolence: dependability1 | Universalism: concern1 | Universalism: nature1 | Universalism: tolerance1 | Self-direction: thought attained2 | Self-direction: thought constrained2 | Self-direction: action attained2 | Self-direction: action constrained2 | Stimulation attained2 | Stimulation constrained2 | Hedonism attained2 | Hedonism constrained2 | Achievement attained2 | Achievement constrained2 | Power: dominance attained2 | Power: dominance constrained2 | Power: resources attained2 | Power: resources constrained2 | Face attained2 | Face constrained2 | Security: personal attained2 | Security: personal constrained2 | Security: societal attained2 | Security: societal constrained2 | Tradition attained2 | Tradition constrained2 | Conformity: rules attained2 | Conformity: rules constrained2 | Conformity: interpersonal attained2 | Conformity: interpersonal constrained2 | Humility attained2 | Humility constrained2 | Benevolence: caring attained2 | Benevolence: caring constrained2 | Benevolence: dependability attained2 | Benevolence: dependability constrained2 | Universalism: concern attained2 | Universalism: concern constrained2 | Universalism: nature attained2 | Universalism: nature constrained2 | Universalism: tolerance attained2 | Universalism: tolerance constrained2 |
112
- |:-------------:|:-----:|:-----:|:---------------:|:------------------:|:------------------:|:-----------------------:|:------------------:|:------------------:|:-----------------------:|:------------------------:|:-----------------------:|:------------:|:---------:|:------------:|:-----------------:|:-----------------:|:------:|:-------------------:|:-------------------:|:----------:|:------------------:|:--------------------------:|:---------:|:--------------------:|:---------------------------:|:----------------------:|:---------------------:|:------------------------:|:---------------------------------:|:------------------------------------:|:--------------------------------:|:-----------------------------------:|:---------------------:|:------------------------:|:------------------:|:---------------------:|:---------------------:|:------------------------:|:--------------------------:|:-----------------------------:|:--------------------------:|:-----------------------------:|:--------------:|:-----------------:|:----------------------------:|:-------------------------------:|:----------------------------:|:-------------------------------:|:-------------------:|:----------------------:|:---------------------------:|:------------------------------:|:-----------------------------------:|:--------------------------------------:|:------------------:|:---------------------:|:-----------------------------:|:--------------------------------:|:------------------------------------:|:---------------------------------------:|:-------------------------------:|:----------------------------------:|:------------------------------:|:---------------------------------:|:---------------------------------:|:------------------------------------:|
113
- | 0.0603 | 1.0 | 7183 | 0.0604 | 0.1393 | 0.2079 | 0.5512 | 0.0485 | 0.0509 | 0.6252 | 0.0 | 0.0431 | 0.0 | 0.0 | 0.2512 | 0.1886 | 0.0844 | 0.2393 | 0.0 | 0.2646 | 0.2359 | 0.3725 | 0.1083 | 0.0 | 0.0277 | 0.0385 | 0.0819 | 0.5374 | 0.1734 | 0.0188 | 0.0137 | 0.0550 | 0.0418 | 0.0530 | 0.0141 | 0.0119 | 0.0110 | 0.1262 | 0.0807 | 0.0659 | 0.0600 | 0.0806 | 0.0833 | 0.0201 | 0.0576 | 0.0161 | 0.0506 | 0.1231 | 0.1471 | 0.0345 | 0.0188 | 0.1007 | 0.0982 | 0.0157 | 0.0351 | 0.0069 | 0.0018 | 0.0476 | 0.0151 | 0.0480 | 0.0142 | 0.0836 | 0.0540 | 0.0380 | 0.0727 | 0.0120 | 0.0166 |
114
- | 0.0411 | 2.0 | 14366 | 0.0607 | 0.2394 | 0.3018 | 0.5948 | 0.0491 | 0.0516 | 0.6270 | 0.0664 | 0.1223 | 0.3371 | 0.3165 | 0.3128 | 0.1460 | 0.1394 | 0.2103 | 0.1218 | 0.4200 | 0.4190 | 0.4399 | 0.0972 | 0.1013 | 0.0874 | 0.1508 | 0.3057 | 0.5369 | 0.2182 | 0.0179 | 0.0375 | 0.0526 | 0.0773 | 0.0589 | 0.0104 | 0.0170 | 0.0059 | 0.1271 | 0.0824 | 0.0694 | 0.0645 | 0.0841 | 0.0744 | 0.0250 | 0.0356 | 0.0180 | 0.0406 | 0.1057 | 0.1696 | 0.0329 | 0.0286 | 0.1114 | 0.0839 | 0.0166 | 0.0295 | 0.0054 | 0.0027 | 0.0439 | 0.0208 | 0.0375 | 0.0203 | 0.0896 | 0.0542 | 0.0477 | 0.0405 | 0.0119 | 0.0158 |
115
- | 0.0282 | 3.0 | 21549 | 0.0599 | 0.2635 | 0.3292 | 0.6016 | 0.0502 | 0.0513 | 0.6128 | 0.0588 | 0.1801 | 0.1815 | 0.2645 | 0.2612 | 0.3455 | 0.2642 | 0.1941 | 0.2454 | 0.4119 | 0.4361 | 0.4578 | 0.0700 | 0.0833 | 0.1117 | 0.2426 | 0.3619 | 0.5693 | 0.2667 | 0.0190 | 0.0561 | 0.0525 | 0.0762 | 0.0631 | 0.0095 | 0.0143 | 0.0071 | 0.1248 | 0.0840 | 0.0701 | 0.0767 | 0.0806 | 0.0807 | 0.0239 | 0.0361 | 0.0187 | 0.0425 | 0.1038 | 0.1802 | 0.0312 | 0.0338 | 0.1044 | 0.0914 | 0.0162 | 0.0294 | 0.0053 | 0.0024 | 0.0438 | 0.0137 | 0.0362 | 0.016 | 0.0852 | 0.0583 | 0.0423 | 0.0516 | 0.0142 | 0.0133 |
116
- | 0.0272 | 4.0 | 28732 | 0.0630 | 0.2883 | 0.3504 | 0.6141 | 0.0492 | 0.0515 | 0.6185 | 0.0935 | 0.2240 | 0.2606 | 0.2857 | 0.3633 | 0.3567 | 0.2972 | 0.2133 | 0.3140 | 0.4242 | 0.4379 | 0.4547 | 0.0662 | 0.0385 | 0.2308 | 0.2571 | 0.3798 | 0.5229 | 0.2577 | 0.0190 | 0.0619 | 0.0525 | 0.0757 | 0.0651 | 0.0137 | 0.0158 | 0.0073 | 0.1216 | 0.0894 | 0.0744 | 0.035 | 0.0804 | 0.0828 | 0.0240 | 0.0343 | 0.0205 | 0.0392 | 0.1079 | 0.1682 | 0.0329 | 0.0220 | 0.1066 | 0.0931 | 0.0159 | 0.0265 | 0.0049 | 0.0023 | 0.0449 | 0.0135 | 0.0355 | 0.0200 | 0.0830 | 0.0601 | 0.0465 | 0.0437 | 0.0126 | 0.0152 |
117
-
118
-
119
  ### Framework versions
120
 
121
  - Transformers 4.37.2
 
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
+ # Human Value Detection Roberta Large with Upsampled Data
15
 
16
+ This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the upsampled training data of the ValueML dataset.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17
 
18
  ### Training hyperparameters
19
 
 
27
  - lr_scheduler_warmup_ratio: 0.2
28
  - num_epochs: 4
29
 
 
 
 
 
 
 
 
 
 
 
30
  ### Framework versions
31
 
32
  - Transformers 4.37.2