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results.txt
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results.txt
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512 Input size - BERTOverflow_UNI_Bin
2021-11-29 15:24:51,106 - root - INFO - Generating metrics for model : BERTOverflow_UNI_Bin
2021-11-29 15:24:51,107 - root - INFO - test metrics
2021-11-29 15:24:55,600 - root - INFO - Accuracy : 69.324760
2021-11-29 15:24:55,635 - root - INFO - Precision macro : 69.353111
2021-11-29 15:24:55,639 - root - INFO - Precision micro : 69.324760
2021-11-29 15:24:55,644 - root - INFO - Recall macro : 69.328644
2021-11-29 15:24:55,648 - root - INFO - Recall micro : 69.324760
2021-11-29 15:24:55,661 - root - INFO - f1 micro : 69.324760
2021-11-29 15:24:55,667 - root - INFO - f1 macro : 69.316162
2021-11-29 15:24:55,693 - root - INFO -
acc: 69.32476043701172
rec_mic: 69.32476043701172
rec_mac: 69.32864379882812
pre_mic: 69.32476043701172
pre_mac: 69.35311126708984
f1_mic: 69.32476043701172
f1_mac: 69.316162109375
BERTOverflow-Multi class
acc: 40.25171661376953
rec_mic: 40.25171661376953
rec_mac: 40.017478942871094
pre_mic: 40.25171661376953
pre_mac: 38.427589416503906
f1_mic: 40.25171661376953
f1_mac: 34.86643981933594
GRU_BIN_ AVG_30
2021-10-29 18:46:56,622 - root - INFO - acc: 76.83367919921875
rec_mic: 76.83367919921875
rec_mac: 76.83365631103516
pre_mic: 76.83367919921875
pre_mac: 76.9711685180664
f1_mic: 76.83368682861328
f1_mac: 76.80394744873047
BERT Binary Classifier
acc: 69.65850830078125
rec_mic: 69.65850830078125
rec_mac: 69.69190979003906
pre_mic: 69.65850830078125
pre_mac: 71.8247299194336
f1_mic: 69.65850830078125
f1_mac: 68.90921783447266
GRU - Multi-class Retrained on balanced set :
acc: 41.05850601196289
rec_mic: 41.05850601196289
rec_mac: 40.81576156616211
pre_mic: 41.05850601196289
pre_mac: 42.36273956298828
f1_mic: 41.05850601196289 f1_mac: 37.070167541503906
BERTOverflow_POS Multi-class:
acc: 39.329673767089844
rec_mic: 39.329673767089844
rec_mac: 39.17381286621094
pre_mic: 39.329673767089844
pre_mac: 39.25950622558594
f1_mic: 39.32967758178711 f1_mac: 36.195152282714844
Multi-class classification problem:
KNN performance over GRU word embeddings :
accuracy: 0.5380572587709188
f1 macro: 0.529821221886155
f1 micro: 0.5380572587709188
recall macro: 0.536143031755987
recall micro: 0.5380572587709188
precision macro: 0.536143031755987
recall micro: 0.5380572587709188
(Binary classification)
KNN performance over GRU word embeddings :
accuracy: 0.7604698961024268
f1 macro: 0.760431658853298
f1 micro: 0.7604698961024268
recall macro: 0.7605002679621923
recall micro: 0.7604698961024268
precision macro: 0.7605002679621923
recall micro: 0.7604698961024268
(Binary classification)
Random forest performance over GRU word embeddings :
accuracy: 0.7658439085097958
f1 macro: 0.76582651938514
f1 micro: 0.7658439085097958
recall macro: 0.7658657468598816
recall micro: 0.7658439085097958
precision macro: 0.7658657468598816
recall micro: 0.7658439085097958
(Multi-class classifcation)
Random forest performance over GRU word embeddings :
accuracy: 0.5785348762159421
f1 macro: 0.5738015453901936
f1 micro: 0.5785348762159421
recall macro: 0.5769526151374171
recall micro: 0.5785348762159421
precision macro: 0.5769526151374171
recall micro: 0.5785348762159421
(Multi-classifcation)
Logistic regression performance over GRU word embeddings :
accuracy: 0.45143146927297034
f1 macro: 0.43279624551378176
f1 micro: 0.45143146927297034
recall macro: 0.44871355186219786
recall micro: 0.45143146927297034
precision macro: 0.44871355186219786
recall micro: 0.45143146927297034
(Binary Classification)
Logistic regression performance over GRU word embeddings :
accuracy: 0.7559349838779628
f1 macro: 0.7556267413635487
f1 micro: 0.7559349838779628
recall macro: 0.7560140911192059
recall micro: 0.7559349838779628
precision macro: 0.7560140911192059
recall micro: 0.7559349838779628
Binary Classifcation
SVC performance over GRU word embeddings :
accuracy: 0.759055682311014
f1 macro: 0.7588361695622508
f1 micro: 0.759055682311014
recall macro: 0.759123413265171
recall micro: 0.759055682311014
precision macro: 0.759123413265171
recall micro: 0.759055682311014
Multiclasss classifcation
SVC performance over GRU word embeddings :
accuracy: 0.5459868148079848
f1 macro: 0.539775985503554
f1 micro: 0.5459868148079848
recall macro: 0.5440432128041431
recall micro: 0.5459868148079848
precision macro: 0.5440432128041431
recall micro: 0.5459868148079848