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Retrain fawiki articlequality model
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Having added sfn templates to fawiki features in T314302,
the fawiki articlequality model has been retrained so that
it can perform better when ref tags are changed to sfn templates.

Bug: T317531
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@kevinbazira
kevinbazira committed Oct 3, 2022
1 parent 1d028cf commit 55bc0f8
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104 changes: 52 additions & 52 deletions model_info/fawiki.wp10.md
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Model Information:
- type: GradientBoosting
- version: 0.8.0
- params: {'tol': 0.0001, 'ccp_alpha': 0.0, 'min_impurity_decrease': 0.0, 'population_rates': None, 'min_weight_fraction_leaf': 0.0, 'max_leaf_nodes': None, 'init': None, 'min_samples_split': 2, 'criterion': 'friedman_mse', 'n_estimators': 100, 'validation_fraction': 0.1, 'warm_start': False, 'learning_rate': 0.5, 'scale': True, 'presort': 'deprecated', 'min_impurity_split': None, 'max_depth': 7, 'min_samples_leaf': 1, 'center': True, 'max_features': 'log2', 'multilabel': False, 'verbose': 0, 'label_weights': None, 'labels': ['Stub', 'Start', 'C', 'B', 'GA', 'FA'], 'n_iter_no_change': None, 'loss': 'deviance', 'random_state': None, 'subsample': 1.0}
- version: 0.9.0
- params: {'scale': True, 'center': True, 'labels': ['Stub', 'Start', 'C', 'B', 'GA', 'FA'], 'multilabel': False, 'population_rates': None, 'ccp_alpha': 0.0, 'criterion': 'friedman_mse', 'init': None, 'learning_rate': 0.5, 'loss': 'deviance', 'max_depth': 7, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 100, 'n_iter_no_change': None, 'presort': 'deprecated', 'random_state': None, 'subsample': 1.0, 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': 0, 'warm_start': False, 'label_weights': None}
Environment:
- revscoring_version: '2.8.2'
- platform: 'Linux-4.9.0-11-amd64-x86_64-with-debian-9.12'
- revscoring_version: '2.11.6'
- platform: 'Linux-4.19.0-20-cloud-amd64-x86_64-with-glibc2.29'
- machine: 'x86_64'
- version: '#1 SMP Debian 4.9.189-3+deb9u1 (2019-09-20)'
- version: '#1 SMP Debian 4.19.235-1 (2022-03-17)'
- system: 'Linux'
- processor: ''
- python_build: ('default', 'Sep 27 2018 17:25:39')
- python_compiler: 'GCC 6.3.0 20170516'
- processor: 'x86_64'
- python_build: ('default', 'Jul 28 2020 12:59:40')
- python_compiler: 'GCC 9.3.0'
- python_branch: ''
- python_implementation: 'CPython'
- python_revision: ''
- python_version: '3.5.3'
- release: '4.9.0-11-amd64'
- python_version: '3.8.5'
- release: '4.19.0-20-cloud-amd64'

Statistics:
counts (n=1235):
counts (n=1229):
label n ~Stub ~Start ~C ~B ~GA ~FA
------- --- --- ------- -------- ---- ---- ----- -----
'Stub' 226 --> 161 21 25 17 1 1
'Start' 94 --> 22 26 33 12 0 1
'C' 152 --> 21 17 57 41 14 2
'B' 200 --> 11 15 29 62 58 25
'GA' 300 --> 1 0 10 42 168 79
'FA' 263 --> 2 0 1 16 83 161
'Stub' 224 --> 142 18 35 26 2 1
'Start' 93 --> 24 21 37 8 3 0
'C' 150 --> 16 21 63 36 12 2
'B' 199 --> 12 14 32 59 54 28
'GA' 300 --> 1 1 11 41 168 78
'FA' 263 --> 0 3 2 23 80 155
rates:
'Stub' 'Start' 'C' 'B' 'GA' 'FA'
---------- -------- --------- ----- ----- ------ ------
sample 0.183 0.076 0.123 0.162 0.243 0.213
sample 0.182 0.076 0.122 0.162 0.244 0.214
population 0.182 0.076 0.123 0.162 0.242 0.212
match_rate (micro=0.187, macro=0.166):
match_rate (micro=0.186, macro=0.166):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.176 0.064 0.125 0.154 0.262 0.218
filter_rate (micro=0.813, macro=0.834):
0.158 0.064 0.147 0.157 0.259 0.214
filter_rate (micro=0.814, macro=0.834):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.824 0.936 0.875 0.846 0.738 0.782
recall (micro=0.514, macro=0.474):
Stub Start C B GA FA
------ ------- ----- ---- ---- -----
0.712 0.277 0.375 0.31 0.56 0.612
!recall (micro=0.891, macro=0.901):
Stub Start C B GA FA
------ ------- ---- ----- ----- -----
0.944 0.954 0.91 0.876 0.833 0.889
precision (micro=0.511, macro=0.479):
0.842 0.936 0.853 0.843 0.741 0.786
recall (micro=0.494, macro=0.454):
Stub Start C B GA FA
------ ------- ---- ----- ---- -----
0.634 0.226 0.42 0.296 0.56 0.589
!recall (micro=0.889, macro=0.897):
Stub Start C B GA FA
------ ------- ----- ---- ----- -----
0.947 0.95 0.892 0.87 0.837 0.887
precision (micro=0.498, macro=0.461):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.737 0.329 0.367 0.326 0.518 0.598
!precision (micro=0.894, macro=0.901):
0.728 0.27 0.352 0.305 0.524 0.585
!precision (micro=0.89, macro=0.898):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.937 0.941 0.912 0.868 0.856 0.895
f1 (micro=0.512, macro=0.476):
0.921 0.937 0.917 0.865 0.856 0.889
f1 (micro=0.495, macro=0.456):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.724 0.3 0.371 0.318 0.538 0.605
!f1 (micro=0.892, macro=0.901):
0.678 0.246 0.383 0.301 0.542 0.587
!f1 (micro=0.889, macro=0.897):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.94 0.947 0.911 0.872 0.844 0.892
accuracy (micro=0.828, macro=0.838):
Stub Start C B GA FA
------ ------- ----- ----- ----- ----
0.902 0.902 0.844 0.785 0.767 0.83
fpr (micro=0.109, macro=0.099):
Stub Start C B GA FA
------ ------- ---- ----- ----- -----
0.056 0.046 0.09 0.124 0.167 0.111
0.934 0.943 0.904 0.868 0.847 0.888
accuracy (micro=0.822, macro=0.832):
Stub Start C B GA FA
------ ------- ----- ----- ---- -----
0.89 0.895 0.834 0.777 0.77 0.824
fpr (micro=0.111, macro=0.103):
Stub Start C B GA FA
------ ------- ----- ---- ----- -----
0.053 0.05 0.108 0.13 0.163 0.113
roc_auc (micro=0.805, macro=0.8):
Stub Start C B GA FA
------ ------- ----- ----- ----- -----
0.929 0.771 0.793 0.694 0.772 0.842
pr_auc (micro=0.485, macro=0.447):
Stub Start C B GA FA
------ ------- ----- ----- ---- -----
0.753 0.228 0.337 0.315 0.48 0.569
0.927 0.782 0.807 0.659 0.79 0.838
pr_auc (micro=0.497, macro=0.455):
Stub Start C B GA FA
------ ------- ----- ---- ----- -----
0.773 0.245 0.326 0.28 0.516 0.591

- score_schema: {'properties': {'probability': {'properties': {'Start': {'type': 'number'}, 'FA': {'type': 'number'}, 'B': {'type': 'number'}, 'GA': {'type': 'number'}, 'Stub': {'type': 'number'}, 'C': {'type': 'number'}}, 'description': 'A mapping of probabilities onto each of the potential output labels', 'type': 'object'}, 'prediction': {'description': 'The most likely label predicted by the estimator', 'type': 'string'}}, 'type': 'object', 'title': 'Scikit learn-based classifier score with probability'}
- score_schema: {'title': 'Scikit learn-based classifier score with probability', 'type': 'object', 'properties': {'prediction': {'description': 'The most likely label predicted by the estimator', 'type': 'string'}, 'probability': {'description': 'A mapping of probabilities onto each of the potential output labels', 'type': 'object', 'properties': {'Stub': {'type': 'number'}, 'Start': {'type': 'number'}, 'C': {'type': 'number'}, 'B': {'type': 'number'}, 'GA': {'type': 'number'}, 'FA': {'type': 'number'}}}}}

4 changes: 2 additions & 2 deletions models/fawiki.wp10.gradient_boosting.model
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