temporal-thyme2-0.7.1 / eval_results.txt
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***** Eval results for task timex *****
acc = 0.9799858455029032
token_f1 = [0.7385976855003403, 0.0, 0.0, 0.0, 0.028169014084507043, 0.0, 0.0, 0.7891593936610014, 0.0, 0.0, 0.8027027027027027, 0.04477611940298507, 0.0, 0.9962215109142981]
f1 = 0.502874834144184
report =
precision recall f1-score support
DATE 0.48 0.69 0.57 1266
DURATION 0.00 0.00 0.00 181
PREPOSTEXP 0.00 0.00 0.00 159
QUANTIFIER 0.00 0.00 0.00 99
SECTIONTIME 0.50 0.94 0.65 279
SET 0.00 0.00 0.00 139
TIME 0.00 0.00 0.00 45
micro avg 0.48 0.52 0.50 2168
macro avg 0.14 0.23 0.17 2168
weighted avg 0.35 0.52 0.41 2168
***** Eval results for task event *****
acc = 0.93882365475203
token_f1 = [0.07663896583564174, 0.7170296060680206, 0.2784452296819788, 0.777024647887324, 0.0, 0.0, 0.0, 0.9858847497089639]
f1 = 0.6977420338108749
report =
precision recall f1-score support
AFTER 0.64 0.04 0.08 2037
BEFORE 0.66 0.77 0.71 7586
BEFORE/OVERLAP 0.94 0.16 0.28 1205
OVERLAP 0.72 0.83 0.77 10556
micro avg 0.70 0.70 0.70 21384
macro avg 0.74 0.45 0.46 21384
weighted avg 0.71 0.70 0.66 21384
***** Eval results for task tlinkx *****
f1 = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9996965951435638, 0.0]
acc = 0.9993933743402987
recall = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0]
precision = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.9993933743402987, 0.0]
report_dict = {'BEFORE': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 300.0}, 'CONTAINS': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 234.0}, 'ENDS-ON': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 125.0}, 'NOTED-ON': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 1231.0}, 'None': {'precision': 0.9993933743402987, 'recall': 1.0, 'f1-score': 0.9996965951435638, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 1219.0}, 'accuracy': 0.9993933743402987, 'macro avg': {'precision': 0.12492417179253734, 'recall': 0.125, 'f1-score': 0.12496207439294547, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9987871166752885, 'recall': 0.9993933743402987, 'f1-score': 0.9990901535370338, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.00 0.00 0.00 921
BEGINS-ON 0.00 0.00 0.00 300
CONTAINS 0.00 0.00 0.00 3282
CONTAINS-SUBEVENT 0.00 0.00 0.00 234
ENDS-ON 0.00 0.00 0.00 125
NOTED-ON 0.00 0.00 0.00 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.00 0.00 0.00 1219
accuracy 1.00 12053562
macro avg 0.12 0.12 0.12 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.993790285144627
token_f1 = [0.921644685802948, 0.7650273224043715, 0.9556962025316456, 0.29508196721311475, 0.9451327433628318, 0.8518518518518519, 0.0, 0.9454960091220068, 0.821826280623608, 0.3875968992248062, 0.9827682045580878, 0.8625235404896422, 0.0, 0.9982044082380304]
f1 = 0.8354831409821225
report =
precision recall f1-score support
DATE 0.85 0.92 0.88 1266
DURATION 0.56 0.73 0.64 181
PREPOSTEXP 0.96 0.95 0.96 159
QUANTIFIER 0.44 0.16 0.24 99
SECTIONTIME 0.89 0.96 0.92 279
SET 0.75 0.83 0.79 139
TIME 0.00 0.00 0.00 45
micro avg 0.82 0.85 0.84 2168
macro avg 0.64 0.65 0.63 2168
weighted avg 0.80 0.85 0.82 2168
***** Eval results for task event *****
acc = 0.9624525329700853
token_f1 = [0.7226107226107226, 0.8515694759255443, 0.6528497409326425, 0.8551680804272699, 0.0, 0.5545454545454546, 0.47342995169082125, 0.9897354608535966]
f1 = 0.8248494045155654
report =
precision recall f1-score support
AFTER 0.68 0.76 0.72 2037
BEFORE 0.88 0.81 0.85 7586
BEFORE/OVERLAP 0.68 0.63 0.65 1205
OVERLAP 0.81 0.90 0.85 10556
micro avg 0.81 0.84 0.82 21384
macro avg 0.76 0.77 0.77 21384
weighted avg 0.81 0.84 0.82 21384
***** Eval results for task tlinkx *****
f1 = [0.0, 0.365, 0.0018264840182648401, 0.0, 0.3493975903614458, 0.09858103061986558, 0.9997018198367735, 0.046215139442231074]
acc = 0.9994032469406139
recall = [0.0, 0.24333333333333335, 0.0009140767824497258, 0.0, 0.232, 0.05361494719740049, 0.9999932759157414, 0.02378999179655455]
precision = [0.0, 0.73, 1.0, 0.0, 0.7073170731707317, 0.6111111111111112, 0.9994105336027373, 0.8055555555555556]
report_dict = {'BEFORE': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.73, 'recall': 0.24333333333333335, 'f1-score': 0.365, 'support': 300.0}, 'CONTAINS': {'precision': 1.0, 'recall': 0.0009140767824497258, 'f1-score': 0.0018264840182648401, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 234.0}, 'ENDS-ON': {'precision': 0.7073170731707317, 'recall': 0.232, 'f1-score': 0.3493975903614458, 'support': 125.0}, 'NOTED-ON': {'precision': 0.6111111111111112, 'recall': 0.05361494719740049, 'f1-score': 0.09858103061986558, 'support': 1231.0}, 'None': {'precision': 0.9994105336027373, 'recall': 0.9999932759157414, 'f1-score': 0.9997018198367735, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.8055555555555556, 'recall': 0.02378999179655455, 'f1-score': 0.046215139442231074, 'support': 1219.0}, 'accuracy': 0.9994032469406139, 'macro avg': {'precision': 0.606674284180017, 'recall': 0.19420570312818494, 'f1-score': 0.2325902580348226, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9992459328658301, 'recall': 0.9994032469406139, 'f1-score': 0.9991233218804325, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.00 0.00 0.00 921
BEGINS-ON 0.73 0.24 0.36 300
CONTAINS 1.00 0.00 0.00 3282
CONTAINS-SUBEVENT 0.00 0.00 0.00 234
ENDS-ON 0.71 0.23 0.35 125
NOTED-ON 0.61 0.05 0.10 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.81 0.02 0.05 1219
accuracy 1.00 12053562
macro avg 0.61 0.19 0.23 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9949850464587122
token_f1 = [0.9296310384176493, 0.8310991957104558, 0.9657320872274143, 0.6, 0.9554367201426025, 0.924187725631769, 0.0, 0.9486166007905138, 0.8910179640718563, 0.6993865030674846, 0.9764705882352941, 0.9467455621301775, 0.02857142857142857, 0.998604963435569]
f1 = 0.8690210102816273
report =
precision recall f1-score support
DATE 0.85 0.96 0.90 1266
DURATION 0.69 0.78 0.73 181
PREPOSTEXP 0.96 0.97 0.97 159
QUANTIFIER 0.61 0.46 0.53 99
SECTIONTIME 0.90 0.96 0.93 279
SET 0.87 0.90 0.88 139
TIME 0.00 0.00 0.00 45
micro avg 0.84 0.90 0.87 2168
macro avg 0.70 0.72 0.71 2168
weighted avg 0.82 0.90 0.86 2168
***** Eval results for task event *****
acc = 0.9681523815321863
token_f1 = [0.784816366773478, 0.8632352941176471, 0.6966205837173579, 0.8784914220898908, 0.0, 0.66, 0.7058823529411765, 0.9912774941128779]
f1 = 0.8501880533557596
report =
precision recall f1-score support
AFTER 0.78 0.78 0.78 2037
BEFORE 0.87 0.85 0.86 7586
BEFORE/OVERLAP 0.65 0.75 0.70 1205
OVERLAP 0.87 0.88 0.88 10556
micro avg 0.85 0.85 0.85 21384
macro avg 0.79 0.81 0.80 21384
weighted avg 0.85 0.85 0.85 21384
***** Eval results for task tlinkx *****
f1 = [0.2232223222322232, 0.5393258426966292, 0.6020362992474546, 0.0, 0.38509316770186336, 0.5560204556020456, 0.9997484948287051, 0.09291698400609291]
acc = 0.9994896114526146
recall = [0.13463626492942454, 0.4, 0.6215722120658135, 0.0, 0.248, 0.48578391551584077, 0.999849413717962, 0.05004101722723544]
precision = [0.6526315789473685, 0.8275862068965517, 0.5836909871244635, 0.0, 0.8611111111111112, 0.65, 0.9996475963097042, 0.648936170212766]
report_dict = {'BEFORE': {'precision': 0.6526315789473685, 'recall': 0.13463626492942454, 'f1-score': 0.2232223222322232, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.8275862068965517, 'recall': 0.4, 'f1-score': 0.5393258426966292, 'support': 300.0}, 'CONTAINS': {'precision': 0.5836909871244635, 'recall': 0.6215722120658135, 'f1-score': 0.6020362992474546, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.0, 'recall': 0.0, 'f1-score': 0.0, 'support': 234.0}, 'ENDS-ON': {'precision': 0.8611111111111112, 'recall': 0.248, 'f1-score': 0.38509316770186336, 'support': 125.0}, 'NOTED-ON': {'precision': 0.65, 'recall': 0.48578391551584077, 'f1-score': 0.5560204556020456, 'support': 1231.0}, 'None': {'precision': 0.9996475963097042, 'recall': 0.999849413717962, 'f1-score': 0.9997484948287051, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.648936170212766, 'recall': 0.05004101722723544, 'f1-score': 0.09291698400609291, 'support': 1219.0}, 'accuracy': 0.9994896114526146, 'macro avg': {'precision': 0.6529504563252457, 'recall': 0.36748535293203455, 'f1-score': 0.4247954457893768, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9994115202205104, 'recall': 0.9994896114526146, 'f1-score': 0.9994066018083547, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.65 0.13 0.22 921
BEGINS-ON 0.83 0.40 0.54 300
CONTAINS 0.58 0.62 0.60 3282
CONTAINS-SUBEVENT 0.00 0.00 0.00 234
ENDS-ON 0.86 0.25 0.39 125
NOTED-ON 0.65 0.49 0.56 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.65 0.05 0.09 1219
accuracy 1.00 12053562
macro avg 0.65 0.37 0.42 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9958221403730395
token_f1 = [0.942714340638216, 0.8739495798319328, 0.9554140127388535, 0.6628571428571428, 0.9557522123893806, 0.9520295202952029, 0.15384615384615385, 0.9556933983163491, 0.908433734939759, 0.770949720670391, 0.9873914261697955, 0.9577464788732394, 0.15789473684210525, 0.998786241931724]
f1 = 0.8839729119638827
report =
precision recall f1-score support
DATE 0.87 0.96 0.91 1266
DURATION 0.78 0.79 0.78 181
PREPOSTEXP 0.97 0.94 0.96 159
QUANTIFIER 0.63 0.53 0.57 99
SECTIONTIME 0.90 0.97 0.93 279
SET 0.93 0.91 0.92 139
TIME 0.33 0.09 0.14 45
micro avg 0.87 0.90 0.88 2168
macro avg 0.77 0.74 0.75 2168
weighted avg 0.86 0.90 0.88 2168
***** Eval results for task event *****
acc = 0.9698798389735707
token_f1 = [0.7794040773653946, 0.8727873820511054, 0.7074536837570012, 0.8842710997442456, 0.3, 0.7914438502673797, 0.708171206225681, 0.9914910269010957]
f1 = 0.858947566158687
report =
precision recall f1-score support
AFTER 0.83 0.73 0.78 2037
BEFORE 0.91 0.83 0.87 7586
BEFORE/OVERLAP 0.74 0.68 0.71 1205
OVERLAP 0.85 0.92 0.88 10556
micro avg 0.86 0.86 0.86 21384
macro avg 0.83 0.79 0.81 21384
weighted avg 0.86 0.86 0.86 21384
***** Eval results for task tlinkx *****
f1 = [0.2719082719082719, 0.5821205821205822, 0.6561687373591447, 0.04580152671755725, 0.46994535519125685, 0.6503616947984844, 0.9997600617489245, 0.17068134893324158]
acc = 0.9995097714683842
recall = [0.18023887079261672, 0.4666666666666667, 0.6919561243144424, 0.02564102564102564, 0.344, 0.7668562144597888, 0.9998098163328837, 0.10172272354388844]
precision = [0.5533333333333333, 0.7734806629834254, 0.6239010989010989, 0.21428571428571427, 0.7413793103448276, 0.5645933014354066, 0.9997103121166979, 0.5299145299145299]
report_dict = {'BEFORE': {'precision': 0.5533333333333333, 'recall': 0.18023887079261672, 'f1-score': 0.2719082719082719, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7734806629834254, 'recall': 0.4666666666666667, 'f1-score': 0.5821205821205822, 'support': 300.0}, 'CONTAINS': {'precision': 0.6239010989010989, 'recall': 0.6919561243144424, 'f1-score': 0.6561687373591447, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.21428571428571427, 'recall': 0.02564102564102564, 'f1-score': 0.04580152671755725, 'support': 234.0}, 'ENDS-ON': {'precision': 0.7413793103448276, 'recall': 0.344, 'f1-score': 0.46994535519125685, 'support': 125.0}, 'NOTED-ON': {'precision': 0.5645933014354066, 'recall': 0.7668562144597888, 'f1-score': 0.6503616947984844, 'support': 1231.0}, 'None': {'precision': 0.9997103121166979, 'recall': 0.9998098163328837, 'f1-score': 0.9997600617489245, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.5299145299145299, 'recall': 0.10172272354388844, 'f1-score': 0.17068134893324158, 'support': 1219.0}, 'accuracy': 0.9995097714683842, 'macro avg': {'precision': 0.6250747829143792, 'recall': 0.4471114302189141, 'f1-score': 0.48084344734718293, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9994583717558536, 'recall': 0.9995097714683842, 'f1-score': 0.9994569547051201, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.55 0.18 0.27 921
BEGINS-ON 0.77 0.47 0.58 300
CONTAINS 0.62 0.69 0.66 3282
CONTAINS-SUBEVENT 0.21 0.03 0.05 234
ENDS-ON 0.74 0.34 0.47 125
NOTED-ON 0.56 0.77 0.65 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.53 0.10 0.17 1219
accuracy 1.00 12053562
macro avg 0.63 0.45 0.48 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9958221403730395
token_f1 = [0.9470795766366131, 0.8657534246575342, 0.9587301587301588, 0.7810650887573964, 0.975177304964539, 0.9285714285714286, 0.47761194029850745, 0.9587881488081978, 0.9106078665077473, 0.8557213930348259, 0.9823874755381604, 0.911487758945386, 0.17647058823529413, 0.9987457992314]
f1 = 0.8815996405302179
report =
precision recall f1-score support
DATE 0.88 0.94 0.91 1266
DURATION 0.75 0.81 0.78 181
PREPOSTEXP 0.97 0.95 0.96 159
QUANTIFIER 0.75 0.65 0.70 99
SECTIONTIME 0.89 0.97 0.93 279
SET 0.81 0.91 0.85 139
TIME 0.25 0.20 0.22 45
micro avg 0.86 0.90 0.88 2168
macro avg 0.76 0.78 0.77 2168
weighted avg 0.86 0.90 0.88 2168
***** Eval results for task event *****
acc = 0.97117352956844
token_f1 = [0.8047846889952153, 0.881969775924961, 0.6880256307569083, 0.8921853790963739, 0.625, 0.8097560975609757, 0.6795366795366795, 0.9917821939948553]
f1 = 0.8658856607310216
report =
precision recall f1-score support
AFTER 0.78 0.82 0.80 2037
BEFORE 0.87 0.89 0.88 7586
BEFORE/OVERLAP 0.66 0.71 0.69 1205
OVERLAP 0.91 0.87 0.89 10556
micro avg 0.87 0.86 0.87 21384
macro avg 0.81 0.82 0.82 21384
weighted avg 0.87 0.86 0.87 21384
***** Eval results for task tlinkx *****
f1 = [0.2663316582914573, 0.610752688172043, 0.6763110307414105, 0.14067278287461774, 0.45652173913043476, 0.6958970233306516, 0.9997787860559014, 0.1986754966887417]
acc = 0.999548598165422
recall = [0.17263843648208468, 0.47333333333333333, 0.6837294332723949, 0.09829059829059829, 0.336, 0.7026807473598701, 0.9998543945211166, 0.12305168170631665]
precision = [0.5824175824175825, 0.8606060606060606, 0.669051878354204, 0.24731182795698925, 0.711864406779661, 0.6892430278884463, 0.9997031890247667, 0.5154639175257731]
report_dict = {'BEFORE': {'precision': 0.5824175824175825, 'recall': 0.17263843648208468, 'f1-score': 0.2663316582914573, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.8606060606060606, 'recall': 0.47333333333333333, 'f1-score': 0.610752688172043, 'support': 300.0}, 'CONTAINS': {'precision': 0.669051878354204, 'recall': 0.6837294332723949, 'f1-score': 0.6763110307414105, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.24731182795698925, 'recall': 0.09829059829059829, 'f1-score': 0.14067278287461774, 'support': 234.0}, 'ENDS-ON': {'precision': 0.711864406779661, 'recall': 0.336, 'f1-score': 0.45652173913043476, 'support': 125.0}, 'NOTED-ON': {'precision': 0.6892430278884463, 'recall': 0.7026807473598701, 'f1-score': 0.6958970233306516, 'support': 1231.0}, 'None': {'precision': 0.9997031890247667, 'recall': 0.9998543945211166, 'f1-score': 0.9997787860559014, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.5154639175257731, 'recall': 0.12305168170631665, 'f1-score': 0.1986754966887417, 'support': 1219.0}, 'accuracy': 0.999548598165422, 'macro avg': {'precision': 0.6594577363191854, 'recall': 0.4486973281207143, 'f1-score': 0.5056176506606573, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9994795414141752, 'recall': 0.999548598165422, 'f1-score': 0.9994906226812705, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.58 0.17 0.27 921
BEGINS-ON 0.86 0.47 0.61 300
CONTAINS 0.67 0.68 0.68 3282
CONTAINS-SUBEVENT 0.25 0.10 0.14 234
ENDS-ON 0.71 0.34 0.46 125
NOTED-ON 0.69 0.70 0.70 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.52 0.12 0.20 1219
accuracy 1.00 12053562
macro avg 0.66 0.45 0.51 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9958678000410937
token_f1 = [0.9420909444228527, 0.8457446808510638, 0.9652996845425867, 0.7027027027027027, 0.9717314487632509, 0.9454545454545454, 0.4383561643835616, 0.9611872146118722, 0.8883977900552487, 0.7878787878787878, 0.9902370990237099, 0.9488188976377953, 0.4424778761061947, 0.9987779385753337]
f1 = 0.8848920863309352
report =
precision recall f1-score support
DATE 0.89 0.94 0.91 1266
DURATION 0.72 0.84 0.78 181
PREPOSTEXP 0.97 0.96 0.97 159
QUANTIFIER 0.60 0.60 0.60 99
SECTIONTIME 0.94 0.99 0.96 279
SET 0.90 0.92 0.91 139
TIME 0.33 0.33 0.33 45
micro avg 0.86 0.91 0.88 2168
macro avg 0.76 0.80 0.78 2168
weighted avg 0.86 0.91 0.89 2168
***** Eval results for task event *****
acc = 0.9720334533167944
token_f1 = [0.8064823641563393, 0.8820368131129921, 0.7421328671328671, 0.8930716481437692, 0.6666666666666666, 0.8102564102564103, 0.725, 0.9917656157590646]
f1 = 0.8706734386756959
report =
precision recall f1-score support
AFTER 0.78 0.83 0.80 2037
BEFORE 0.90 0.86 0.88 7586
BEFORE/OVERLAP 0.78 0.70 0.74 1205
OVERLAP 0.89 0.89 0.89 10556
micro avg 0.88 0.87 0.87 21384
macro avg 0.84 0.82 0.83 21384
weighted avg 0.88 0.87 0.87 21384
***** Eval results for task tlinkx *****
f1 = [0.29307568438003223, 0.6209677419354839, 0.6979390956628729, 0.125, 0.49162011173184356, 0.702475870751154, 0.9997883335425096, 0.1899070385126162]
acc = 0.999567928550913
recall = [0.1976112920738328, 0.5133333333333333, 0.6913467397928093, 0.0811965811965812, 0.352, 0.6799350121852152, 0.9998718273321573, 0.1173092698933552]
precision = [0.5669781931464174, 0.7857142857142857, 0.7046583850931677, 0.2714285714285714, 0.8148148148148148, 0.7265625, 0.9997048536959107, 0.49825783972125437]
report_dict = {'BEFORE': {'precision': 0.5669781931464174, 'recall': 0.1976112920738328, 'f1-score': 0.29307568438003223, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7857142857142857, 'recall': 0.5133333333333333, 'f1-score': 0.6209677419354839, 'support': 300.0}, 'CONTAINS': {'precision': 0.7046583850931677, 'recall': 0.6913467397928093, 'f1-score': 0.6979390956628729, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.2714285714285714, 'recall': 0.0811965811965812, 'f1-score': 0.125, 'support': 234.0}, 'ENDS-ON': {'precision': 0.8148148148148148, 'recall': 0.352, 'f1-score': 0.49162011173184356, 'support': 125.0}, 'NOTED-ON': {'precision': 0.7265625, 'recall': 0.6799350121852152, 'f1-score': 0.702475870751154, 'support': 1231.0}, 'None': {'precision': 0.9997048536959107, 'recall': 0.9998718273321573, 'f1-score': 0.9997883335425096, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.49825783972125437, 'recall': 0.1173092698933552, 'f1-score': 0.1899070385126162, 'support': 1219.0}, 'accuracy': 0.999567928550913, 'macro avg': {'precision': 0.6710149304518027, 'recall': 0.45407550697591054, 'f1-score': 0.5150967345645641, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9994914635804361, 'recall': 0.999567928550913, 'f1-score': 0.999508195923091, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.57 0.20 0.29 921
BEGINS-ON 0.79 0.51 0.62 300
CONTAINS 0.70 0.69 0.70 3282
CONTAINS-SUBEVENT 0.27 0.08 0.12 234
ENDS-ON 0.81 0.35 0.49 125
NOTED-ON 0.73 0.68 0.70 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.50 0.12 0.19 1219
accuracy 1.00 12053562
macro avg 0.67 0.45 0.52 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9960960983813648
token_f1 = [0.9455115640925127, 0.8681318681318682, 0.9587301587301588, 0.6745562130177515, 0.9769094138543517, 0.9446494464944649, 0.46153846153846156, 0.9683257918552036, 0.9248826291079812, 0.7597765363128491, 0.9856540084388186, 0.9558232931726908, 0.3125, 0.9988226832375006]
f1 = 0.8911116162764265
report =
precision recall f1-score support
DATE 0.90 0.94 0.92 1266
DURATION 0.78 0.85 0.81 181
PREPOSTEXP 0.97 0.95 0.96 159
QUANTIFIER 0.65 0.52 0.57 99
SECTIONTIME 0.94 0.97 0.95 279
SET 0.91 0.90 0.90 139
TIME 0.27 0.29 0.28 45
micro avg 0.88 0.90 0.89 2168
macro avg 0.77 0.77 0.77 2168
weighted avg 0.88 0.90 0.89 2168
***** Eval results for task event *****
acc = 0.9715768566362523
token_f1 = [0.8040687817873577, 0.8803781858043299, 0.738509076863654, 0.891389983117614, 0.6415094339622641, 0.8241206030150754, 0.6810344827586207, 0.9918340221765016]
f1 = 0.8679280673372254
report =
precision recall f1-score support
AFTER 0.79 0.81 0.80 2037
BEFORE 0.91 0.85 0.88 7586
BEFORE/OVERLAP 0.69 0.79 0.74 1205
OVERLAP 0.88 0.90 0.89 10556
micro avg 0.87 0.87 0.87 21384
macro avg 0.82 0.84 0.83 21384
weighted avg 0.87 0.87 0.87 21384
***** Eval results for task tlinkx *****
f1 = [0.33640880056777855, 0.6536203522504892, 0.7054409005628518, 0.20178041543026706, 0.5026178010471204, 0.722010662604722, 0.9997896985667005, 0.2531493701259748]
acc = 0.999568509292108
recall = [0.25732899022801303, 0.5566666666666666, 0.6873857404021938, 0.1452991452991453, 0.384, 0.7701056051990252, 0.9998514060392238, 0.17309269893355209]
precision = [0.48565573770491804, 0.7914691943127962, 0.7244701348747592, 0.3300970873786408, 0.7272727272727273, 0.6795698924731183, 0.9997279987104633, 0.47098214285714285]
report_dict = {'BEFORE': {'precision': 0.48565573770491804, 'recall': 0.25732899022801303, 'f1-score': 0.33640880056777855, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7914691943127962, 'recall': 0.5566666666666666, 'f1-score': 0.6536203522504892, 'support': 300.0}, 'CONTAINS': {'precision': 0.7244701348747592, 'recall': 0.6873857404021938, 'f1-score': 0.7054409005628518, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.3300970873786408, 'recall': 0.1452991452991453, 'f1-score': 0.20178041543026706, 'support': 234.0}, 'ENDS-ON': {'precision': 0.7272727272727273, 'recall': 0.384, 'f1-score': 0.5026178010471204, 'support': 125.0}, 'NOTED-ON': {'precision': 0.6795698924731183, 'recall': 0.7701056051990252, 'f1-score': 0.722010662604722, 'support': 1231.0}, 'None': {'precision': 0.9997279987104633, 'recall': 0.9998514060392238, 'f1-score': 0.9997896985667005, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.47098214285714285, 'recall': 0.17309269893355209, 'f1-score': 0.2531493701259748, 'support': 1219.0}, 'accuracy': 0.999568509292108, 'macro avg': {'precision': 0.6511556144480708, 'recall': 0.49671628159597747, 'f1-score': 0.546852250144488, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9995065918871474, 'recall': 0.999568509292108, 'f1-score': 0.9995257219447622, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.49 0.26 0.34 921
BEGINS-ON 0.79 0.56 0.65 300
CONTAINS 0.72 0.69 0.71 3282
CONTAINS-SUBEVENT 0.33 0.15 0.20 234
ENDS-ON 0.73 0.38 0.50 125
NOTED-ON 0.68 0.77 0.72 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.47 0.17 0.25 1219
accuracy 1.00 12053562
macro avg 0.65 0.50 0.55 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9963243967216359
token_f1 = [0.9476971116315379, 0.8681318681318682, 0.9652996845425867, 0.7570621468926554, 0.9786476868327402, 0.9520295202952029, 0.47368421052631576, 0.967712596634834, 0.9150174621653085, 0.826530612244898, 0.9871003925967471, 0.9582504970178927, 0.3484848484848485, 0.9989430577379828]
f1 = 0.8950827101744844
report =
precision recall f1-score support
DATE 0.90 0.94 0.92 1266
DURATION 0.79 0.85 0.82 181
PREPOSTEXP 0.97 0.96 0.97 159
QUANTIFIER 0.67 0.61 0.63 99
SECTIONTIME 0.95 0.98 0.96 279
SET 0.92 0.91 0.92 139
TIME 0.28 0.31 0.29 45
micro avg 0.88 0.91 0.90 2168
macro avg 0.78 0.79 0.79 2168
weighted avg 0.88 0.91 0.89 2168
***** Eval results for task event *****
acc = 0.9723074113251197
token_f1 = [0.8126077320856931, 0.8837178814892501, 0.7230639730639731, 0.8948974725798761, 0.6538461538461539, 0.8140703517587939, 0.7301587301587301, 0.991996284965035]
f1 = 0.8716783052912781
report =
precision recall f1-score support
AFTER 0.81 0.81 0.81 2037
BEFORE 0.88 0.89 0.88 7586
BEFORE/OVERLAP 0.73 0.71 0.72 1205
OVERLAP 0.90 0.89 0.89 10556
micro avg 0.87 0.87 0.87 21384
macro avg 0.83 0.82 0.83 21384
weighted avg 0.87 0.87 0.87 21384
***** Eval results for task tlinkx *****
f1 = [0.3630229419703104, 0.6527514231499051, 0.713383643924226, 0.17034700315457413, 0.5238095238095238, 0.7317466720451795, 0.9997931435212086, 0.24133663366336633]
acc = 0.9995758100385596
recall = [0.2920738327904452, 0.5733333333333334, 0.7056672760511883, 0.11538461538461539, 0.44, 0.7367993501218522, 0.9998553906817474, 0.15996718621821165]
precision = [0.47950089126559714, 0.7577092511013216, 0.7212706322018063, 0.3253012048192771, 0.6470588235294118, 0.7267628205128205, 0.9997309041107261, 0.491183879093199]
report_dict = {'BEFORE': {'precision': 0.47950089126559714, 'recall': 0.2920738327904452, 'f1-score': 0.3630229419703104, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7577092511013216, 'recall': 0.5733333333333334, 'f1-score': 0.6527514231499051, 'support': 300.0}, 'CONTAINS': {'precision': 0.7212706322018063, 'recall': 0.7056672760511883, 'f1-score': 0.713383643924226, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.3253012048192771, 'recall': 0.11538461538461539, 'f1-score': 0.17034700315457413, 'support': 234.0}, 'ENDS-ON': {'precision': 0.6470588235294118, 'recall': 0.44, 'f1-score': 0.5238095238095238, 'support': 125.0}, 'NOTED-ON': {'precision': 0.7267628205128205, 'recall': 0.7367993501218522, 'f1-score': 0.7317466720451795, 'support': 1231.0}, 'None': {'precision': 0.9997309041107261, 'recall': 0.9998553906817474, 'f1-score': 0.9997931435212086, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.491183879093199, 'recall': 0.15996718621821165, 'f1-score': 0.24133663366336633, 'support': 1219.0}, 'accuracy': 0.9995758100385596, 'macro avg': {'precision': 0.6435648008292699, 'recall': 0.5028851230726742, 'f1-score': 0.5495238731547867, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9995132515990246, 'recall': 0.9995758100385596, 'f1-score': 0.9995327486362252, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.48 0.29 0.36 921
BEGINS-ON 0.76 0.57 0.65 300
CONTAINS 0.72 0.71 0.71 3282
CONTAINS-SUBEVENT 0.33 0.12 0.17 234
ENDS-ON 0.65 0.44 0.52 125
NOTED-ON 0.73 0.74 0.73 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.49 0.16 0.24 1219
accuracy 1.00 12053562
macro avg 0.64 0.50 0.55 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9962330773855274
token_f1 = [0.9456394211967148, 0.8666666666666667, 0.9652996845425867, 0.7333333333333333, 0.9769094138543517, 0.9481481481481482, 0.4473684210526316, 0.967391304347826, 0.9205607476635514, 0.8082901554404145, 0.9871148459383754, 0.9596774193548387, 0.3089430894308943, 0.9988948588835261]
f1 = 0.8937812074443939
report =
precision recall f1-score support
DATE 0.90 0.94 0.92 1266
DURATION 0.80 0.84 0.82 181
PREPOSTEXP 0.97 0.96 0.97 159
QUANTIFIER 0.62 0.59 0.60 99
SECTIONTIME 0.94 0.98 0.96 279
SET 0.94 0.90 0.92 139
TIME 0.24 0.27 0.26 45
micro avg 0.88 0.91 0.89 2168
macro avg 0.77 0.78 0.78 2168
weighted avg 0.88 0.91 0.89 2168
***** Eval results for task event *****
acc = 0.9722541417123898
token_f1 = [0.8115595892046812, 0.8836833602584814, 0.7373233582709892, 0.8940456578018358, 0.6538461538461539, 0.8223350253807107, 0.7116104868913857, 0.9919764667310249]
f1 = 0.8714442909652799
report =
precision recall f1-score support
AFTER 0.79 0.83 0.81 2037
BEFORE 0.90 0.86 0.88 7586
BEFORE/OVERLAP 0.74 0.74 0.74 1205
OVERLAP 0.89 0.90 0.89 10556
micro avg 0.87 0.87 0.87 21384
macro avg 0.83 0.83 0.83 21384
weighted avg 0.87 0.87 0.87 21384
***** Eval results for task tlinkx *****
f1 = [0.3551532033426184, 0.6679174484052532, 0.713523402957768, 0.1978021978021978, 0.5288461538461539, 0.7362505018065034, 0.9997928094933096, 0.2810198300283286]
acc = 0.9995731552216681
recall = [0.2768729641693811, 0.5933333333333334, 0.7129798903107861, 0.15384615384615385, 0.44, 0.7449228269699432, 0.9998454290754384, 0.20344544708777687]
precision = [0.49514563106796117, 0.7639484978540773, 0.7140677448886177, 0.27692307692307694, 0.6626506024096386, 0.7277777777777777, 0.9997401954493863, 0.4542124542124542]
report_dict = {'BEFORE': {'precision': 0.49514563106796117, 'recall': 0.2768729641693811, 'f1-score': 0.3551532033426184, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7639484978540773, 'recall': 0.5933333333333334, 'f1-score': 0.6679174484052532, 'support': 300.0}, 'CONTAINS': {'precision': 0.7140677448886177, 'recall': 0.7129798903107861, 'f1-score': 0.713523402957768, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.27692307692307694, 'recall': 0.15384615384615385, 'f1-score': 0.1978021978021978, 'support': 234.0}, 'ENDS-ON': {'precision': 0.6626506024096386, 'recall': 0.44, 'f1-score': 0.5288461538461539, 'support': 125.0}, 'NOTED-ON': {'precision': 0.7277777777777777, 'recall': 0.7449228269699432, 'f1-score': 0.7362505018065034, 'support': 1231.0}, 'None': {'precision': 0.9997401954493863, 'recall': 0.9998454290754384, 'f1-score': 0.9997928094933096, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.4542124542124542, 'recall': 0.20344544708777687, 'f1-score': 0.2810198300283286, 'support': 1219.0}, 'accuracy': 0.9995731552216681, 'macro avg': {'precision': 0.6368082475728738, 'recall': 0.5156557555991016, 'f1-score': 0.5600381934602666, 'support': 12053562.0}, 'weighted avg': {'precision': 0.999517513926414, 'recall': 0.9995731552216681, 'f1-score': 0.9995372874446685, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.50 0.28 0.36 921
BEGINS-ON 0.76 0.59 0.67 300
CONTAINS 0.71 0.71 0.71 3282
CONTAINS-SUBEVENT 0.28 0.15 0.20 234
ENDS-ON 0.66 0.44 0.53 125
NOTED-ON 0.73 0.74 0.74 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.45 0.20 0.28 1219
accuracy 1.00 12053562
macro avg 0.64 0.52 0.56 12053562
weighted avg 1.00 1.00 1.00 12053562
***** Eval results for task timex *****
acc = 0.9962863469982574
token_f1 = [0.9467133411124076, 0.8746518105849582, 0.9717868338557993, 0.73224043715847, 0.9769094138543517, 0.9516728624535316, 0.4266666666666667, 0.9680923285811269, 0.9263157894736842, 0.8167539267015707, 0.9862629660779366, 0.9617706237424547, 0.30158730158730157, 0.9989068402861506]
f1 = 0.8956305184514375
report =
precision recall f1-score support
DATE 0.90 0.95 0.92 1266
DURATION 0.81 0.85 0.83 181
PREPOSTEXP 0.97 0.97 0.97 159
QUANTIFIER 0.62 0.59 0.60 99
SECTIONTIME 0.94 0.98 0.96 279
SET 0.94 0.90 0.92 139
TIME 0.24 0.27 0.25 45
micro avg 0.88 0.91 0.90 2168
macro avg 0.78 0.79 0.78 2168
weighted avg 0.88 0.91 0.90 2168
***** Eval results for task event *****
acc = 0.9724063406059038
token_f1 = [0.8119243819680078, 0.8850328286211979, 0.7399507793273175, 0.8942812544345111, 0.6415094339622641, 0.8223350253807107, 0.714859437751004, 0.9919611806048688]
f1 = 0.8724382122590628
report =
precision recall f1-score support
AFTER 0.80 0.82 0.81 2037
BEFORE 0.90 0.87 0.88 7586
BEFORE/OVERLAP 0.73 0.75 0.74 1205
OVERLAP 0.89 0.89 0.89 10556
micro avg 0.87 0.87 0.87 21384
macro avg 0.83 0.83 0.83 21384
weighted avg 0.88 0.87 0.87 21384
***** Eval results for task tlinkx *****
f1 = [0.36606546426185704, 0.6666666666666666, 0.7110640230059029, 0.2185792349726776, 0.5308056872037915, 0.7366758784050533, 0.999791314135728, 0.284077892325315]
acc = 0.9995700026266094
recall = [0.2975027144408252, 0.5933333333333334, 0.7157221206581352, 0.17094017094017094, 0.448, 0.7579203899268887, 0.9998382069108643, 0.20344544708777687]
precision = [0.4756944444444444, 0.7606837606837606, 0.7064661654135338, 0.30303030303030304, 0.6511627906976745, 0.716589861751152, 0.9997444257589617, 0.47058823529411764]
report_dict = {'BEFORE': {'precision': 0.4756944444444444, 'recall': 0.2975027144408252, 'f1-score': 0.36606546426185704, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7606837606837606, 'recall': 0.5933333333333334, 'f1-score': 0.6666666666666666, 'support': 300.0}, 'CONTAINS': {'precision': 0.7064661654135338, 'recall': 0.7157221206581352, 'f1-score': 0.7110640230059029, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.30303030303030304, 'recall': 0.17094017094017094, 'f1-score': 0.2185792349726776, 'support': 234.0}, 'ENDS-ON': {'precision': 0.6511627906976745, 'recall': 0.448, 'f1-score': 0.5308056872037915, 'support': 125.0}, 'NOTED-ON': {'precision': 0.716589861751152, 'recall': 0.7579203899268887, 'f1-score': 0.7366758784050533, 'support': 1231.0}, 'None': {'precision': 0.9997444257589617, 'recall': 0.9998382069108643, 'f1-score': 0.999791314135728, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.47058823529411764, 'recall': 0.20344544708777687, 'f1-score': 0.284077892325315, 'support': 1219.0}, 'accuracy': 0.9995700026266094, 'macro avg': {'precision': 0.6354949983842435, 'recall': 0.5233377979122493, 'f1-score': 0.564215770122124, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9995190055921814, 'recall': 0.9995700026266094, 'f1-score': 0.9995367023899284, 'support': 12053562.0}}
report_str = precision recall f1-score support
BEFORE 0.48 0.30 0.37 921
BEGINS-ON 0.76 0.59 0.67 300
CONTAINS 0.71 0.72 0.71 3282
CONTAINS-SUBEVENT 0.30 0.17 0.22 234
ENDS-ON 0.65 0.45 0.53 125
NOTED-ON 0.72 0.76 0.74 1231
None 1.00 1.00 1.00 12046250
OVERLAP 0.47 0.20 0.28 1219
accuracy 1.00 12053562
macro avg 0.64 0.52 0.56 12053562
weighted avg 1.00 1.00 1.00 12053562
timex = {'acc': 0.9962863469982574, 'token_f1': [0.9467133411124076, 0.8746518105849582, 0.9717868338557993, 0.73224043715847, 0.9769094138543517, 0.9516728624535316, 0.4266666666666667, 0.9680923285811269, 0.9263157894736842, 0.8167539267015707, 0.9862629660779366, 0.9617706237424547, 0.30158730158730157, 0.9989068402861506], 'f1': 0.8956305184514375, 'report': '\n precision recall f1-score support\n\n DATE 0.90 0.95 0.92 1266\n DURATION 0.81 0.85 0.83 181\n PREPOSTEXP 0.97 0.97 0.97 159\n QUANTIFIER 0.62 0.59 0.60 99\n SECTIONTIME 0.94 0.98 0.96 279\n SET 0.94 0.90 0.92 139\n TIME 0.24 0.27 0.25 45\n\n micro avg 0.88 0.91 0.90 2168\n macro avg 0.78 0.79 0.78 2168\nweighted avg 0.88 0.91 0.90 2168\n'}
event = {'acc': 0.9724063406059038, 'token_f1': [0.8119243819680078, 0.8850328286211979, 0.7399507793273175, 0.8942812544345111, 0.6415094339622641, 0.8223350253807107, 0.714859437751004, 0.9919611806048688], 'f1': 0.8724382122590628, 'report': '\n precision recall f1-score support\n\n AFTER 0.80 0.82 0.81 2037\n BEFORE 0.90 0.87 0.88 7586\nBEFORE/OVERLAP 0.73 0.75 0.74 1205\n OVERLAP 0.89 0.89 0.89 10556\n\n micro avg 0.87 0.87 0.87 21384\n macro avg 0.83 0.83 0.83 21384\n weighted avg 0.88 0.87 0.87 21384\n'}
tlinkx = {'f1': [0.36606546426185704, 0.6666666666666666, 0.7110640230059029, 0.2185792349726776, 0.5308056872037915, 0.7366758784050533, 0.999791314135728, 0.284077892325315], 'acc': 0.9995700026266094, 'recall': [0.2975027144408252, 0.5933333333333334, 0.7157221206581352, 0.17094017094017094, 0.448, 0.7579203899268887, 0.9998382069108643, 0.20344544708777687], 'precision': [0.4756944444444444, 0.7606837606837606, 0.7064661654135338, 0.30303030303030304, 0.6511627906976745, 0.716589861751152, 0.9997444257589617, 0.47058823529411764], 'report_dict': {'BEFORE': {'precision': 0.4756944444444444, 'recall': 0.2975027144408252, 'f1-score': 0.36606546426185704, 'support': 921.0}, 'BEGINS-ON': {'precision': 0.7606837606837606, 'recall': 0.5933333333333334, 'f1-score': 0.6666666666666666, 'support': 300.0}, 'CONTAINS': {'precision': 0.7064661654135338, 'recall': 0.7157221206581352, 'f1-score': 0.7110640230059029, 'support': 3282.0}, 'CONTAINS-SUBEVENT': {'precision': 0.30303030303030304, 'recall': 0.17094017094017094, 'f1-score': 0.2185792349726776, 'support': 234.0}, 'ENDS-ON': {'precision': 0.6511627906976745, 'recall': 0.448, 'f1-score': 0.5308056872037915, 'support': 125.0}, 'NOTED-ON': {'precision': 0.716589861751152, 'recall': 0.7579203899268887, 'f1-score': 0.7366758784050533, 'support': 1231.0}, 'None': {'precision': 0.9997444257589617, 'recall': 0.9998382069108643, 'f1-score': 0.999791314135728, 'support': 12046250.0}, 'OVERLAP': {'precision': 0.47058823529411764, 'recall': 0.20344544708777687, 'f1-score': 0.284077892325315, 'support': 1219.0}, 'accuracy': 0.9995700026266094, 'macro avg': {'precision': 0.6354949983842435, 'recall': 0.5233377979122493, 'f1-score': 0.564215770122124, 'support': 12053562.0}, 'weighted avg': {'precision': 0.9995190055921814, 'recall': 0.9995700026266094, 'f1-score': 0.9995367023899284, 'support': 12053562.0}}, 'report_str': ' precision recall f1-score support\n\n BEFORE 0.48 0.30 0.37 921\n BEGINS-ON 0.76 0.59 0.67 300\n CONTAINS 0.71 0.72 0.71 3282\nCONTAINS-SUBEVENT 0.30 0.17 0.22 234\n ENDS-ON 0.65 0.45 0.53 125\n NOTED-ON 0.72 0.76 0.74 1231\n None 1.00 1.00 1.00 12046250\n OVERLAP 0.47 0.20 0.28 1219\n\n accuracy 1.00 12053562\n macro avg 0.64 0.52 0.56 12053562\n weighted avg 1.00 1.00 1.00 12053562\n'}
Current state (In Compute Metrics Function)
best_score : 0.7774281669442081
curr_epoch : 9.912536443148689
max_epochs : 10
curr_step : 850
max_steps : 850
best_step : 850
best_epoch : 9.912536443148689