初始化项目,由ModelHub XC社区提供模型

Model: penupup/quora-distilbert-multilingual-lcqmc-sfa-hr
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-10-30 15:34:26 +08:00
commit 71ac415932
20 changed files with 239545 additions and 0 deletions

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epoch,steps,cossim_accuracy,cossim_accuracy_threshold,cossim_f1,cossim_precision,cossim_recall,cossim_f1_threshold,cossim_ap,manhatten_accuracy,manhatten_accuracy_threshold,manhatten_f1,manhatten_precision,manhatten_recall,manhatten_f1_threshold,manhatten_ap,euclidean_accuracy,euclidean_accuracy_threshold,euclidean_f1,euclidean_precision,euclidean_recall,euclidean_f1_threshold,euclidean_ap,dot_accuracy,dot_accuracy_threshold,dot_f1,dot_precision,dot_recall,dot_f1_threshold,dot_ap
0,-1,0.8785046728971962,0.7153000831604004,0.7941176470588236,0.675,0.9642857142857143,0.5783578157424927,0.7578364440157217,0.8878504672897196,138.98406982421875,0.793103448275862,0.7666666666666667,0.8214285714285714,143.1756591796875,0.7458732145200913,0.8878504672897196,6.292994499206543,0.7868852459016394,0.7272727272727273,0.8571428571428571,6.918923377990723,0.7407456621713792,0.8504672897196262,50.74915313720703,0.7605633802816901,0.627906976744186,0.9642857142857143,38.95372009277344,0.7650624140372936
1,-1,0.8785046728971962,0.7153072357177734,0.7941176470588236,0.675,0.9642857142857143,0.5788319110870361,0.7584630104317618,0.8878504672897196,139.05062866210938,0.793103448275862,0.7666666666666667,0.8214285714285714,143.0370635986328,0.7458732145200913,0.8878504672897196,6.295968055725098,0.7868852459016394,0.7272727272727273,0.8571428571428571,6.918813705444336,0.7407456621713792,0.8504672897196262,50.75468444824219,0.7605633802816901,0.627906976744186,0.9642857142857143,38.996490478515625,0.7661446651195446
2,-1,0.8785046728971962,0.7151119709014893,0.7941176470588236,0.675,0.9642857142857143,0.5796480178833008,0.7584630104317618,0.8878504672897196,139.16299438476562,0.793103448275862,0.7666666666666667,0.8214285714285714,142.8717803955078,0.7458732145200913,0.8878504672897196,6.300694942474365,0.7868852459016394,0.7272727272727273,0.8571428571428571,6.920260906219482,0.7420011467777131,0.8598130841121495,49.97108459472656,0.7605633802816901,0.627906976744186,0.9642857142857143,39.10533142089844,0.7690771274598031
3,-1,0.8785046728971962,0.7149893045425415,0.7941176470588236,0.675,0.9642857142857143,0.5805591344833374,0.7584630104317618,0.8878504672897196,139.26937866210938,0.793103448275862,0.7666666666666667,0.8214285714285714,142.61703491210938,0.7464071490241253,0.897196261682243,6.417535781860352,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.417535781860352,0.743486466982473,0.8598130841121495,50.244720458984375,0.7605633802816901,0.627906976744186,0.9642857142857143,39.23603057861328,0.7700890322217079
4,-1,0.8785046728971962,0.7147645950317383,0.7941176470588236,0.675,0.9642857142857143,0.581954836845398,0.7584630104317618,0.897196261682243,140.93128967285156,0.7999999999999999,0.8148148148148148,0.7857142857142857,140.93128967285156,0.746734202922608,0.897196261682243,6.424378871917725,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.424378871917725,0.7439523054917898,0.8598130841121495,50.70547866821289,0.7714285714285715,0.6428571428571429,0.9642857142857143,40.70288848876953,0.7732340939525525
5,-1,0.8785046728971962,0.7756680846214294,0.7941176470588236,0.675,0.9642857142857143,0.5837556719779968,0.7596923064980143,0.897196261682243,140.8372802734375,0.8070175438596492,0.7931034482758621,0.8214285714285714,141.61801147460938,0.7476783736943649,0.897196261682243,6.431297302246094,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.431297302246094,0.7439523054917898,0.8598130841121495,51.126739501953125,0.7714285714285715,0.6428571428571429,0.9642857142857143,40.991600036621094,0.7742007199191785
6,-1,0.8785046728971962,0.7758897542953491,0.7941176470588236,0.675,0.9642857142857143,0.5853708982467651,0.7596870261600728,0.897196261682243,140.56597900390625,0.8070175438596492,0.7931034482758621,0.8214285714285714,141.67572021484375,0.7482383537839616,0.897196261682243,6.416640281677246,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.416640281677246,0.7472146926888119,0.8598130841121495,53.09589767456055,0.7714285714285715,0.6428571428571429,0.9642857142857143,41.28678894042969,0.7718897142696635
7,-1,0.8785046728971962,0.7762866020202637,0.7941176470588236,0.675,0.9642857142857143,0.5878200531005859,0.7596870261600728,0.897196261682243,140.15020751953125,0.8070175438596492,0.7931034482758621,0.8214285714285714,141.2872314453125,0.7510123833437055,0.897196261682243,6.113794326782227,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.399294853210449,0.7495590150331343,0.8598130841121495,53.3231201171875,0.7714285714285715,0.6428571428571429,0.9642857142857143,41.694549560546875,0.7764593657594636
8,-1,0.8878504672897196,0.6951338052749634,0.7999999999999999,0.7027027027027027,0.9285714285714286,0.6463806629180908,0.761901030729765,0.897196261682243,139.57412719726562,0.8070175438596492,0.7931034482758621,0.8214285714285714,140.79031372070312,0.7522028595341816,0.897196261682243,6.1220855712890625,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.377052307128906,0.7518712111606615,0.8598130841121495,53.603271484375,0.7714285714285715,0.6428571428571429,0.9642857142857143,42.17536163330078,0.7778469140220119
9,-1,0.8878504672897196,0.697858452796936,0.8059701492537313,0.6923076923076923,0.9642857142857143,0.6171824336051941,0.7629305664756872,0.897196261682243,135.81292724609375,0.8070175438596492,0.7931034482758621,0.8214285714285714,140.23594665527344,0.7548442564499593,0.897196261682243,6.1298041343688965,0.7999999999999999,0.8148148148148148,0.7857142857142857,6.352500915527344,0.7539231117088027,0.8598130841121495,53.983299255371094,0.782608695652174,0.6585365853658537,0.9642857142857143,43.110023498535156,0.7775448251460915
1 epoch steps cossim_accuracy cossim_accuracy_threshold cossim_f1 cossim_precision cossim_recall cossim_f1_threshold cossim_ap manhatten_accuracy manhatten_accuracy_threshold manhatten_f1 manhatten_precision manhatten_recall manhatten_f1_threshold manhatten_ap euclidean_accuracy euclidean_accuracy_threshold euclidean_f1 euclidean_precision euclidean_recall euclidean_f1_threshold euclidean_ap dot_accuracy dot_accuracy_threshold dot_f1 dot_precision dot_recall dot_f1_threshold dot_ap
2 0 -1 0.8785046728971962 0.7153000831604004 0.7941176470588236 0.675 0.9642857142857143 0.5783578157424927 0.7578364440157217 0.8878504672897196 138.98406982421875 0.793103448275862 0.7666666666666667 0.8214285714285714 143.1756591796875 0.7458732145200913 0.8878504672897196 6.292994499206543 0.7868852459016394 0.7272727272727273 0.8571428571428571 6.918923377990723 0.7407456621713792 0.8504672897196262 50.74915313720703 0.7605633802816901 0.627906976744186 0.9642857142857143 38.95372009277344 0.7650624140372936
3 1 -1 0.8785046728971962 0.7153072357177734 0.7941176470588236 0.675 0.9642857142857143 0.5788319110870361 0.7584630104317618 0.8878504672897196 139.05062866210938 0.793103448275862 0.7666666666666667 0.8214285714285714 143.0370635986328 0.7458732145200913 0.8878504672897196 6.295968055725098 0.7868852459016394 0.7272727272727273 0.8571428571428571 6.918813705444336 0.7407456621713792 0.8504672897196262 50.75468444824219 0.7605633802816901 0.627906976744186 0.9642857142857143 38.996490478515625 0.7661446651195446
4 2 -1 0.8785046728971962 0.7151119709014893 0.7941176470588236 0.675 0.9642857142857143 0.5796480178833008 0.7584630104317618 0.8878504672897196 139.16299438476562 0.793103448275862 0.7666666666666667 0.8214285714285714 142.8717803955078 0.7458732145200913 0.8878504672897196 6.300694942474365 0.7868852459016394 0.7272727272727273 0.8571428571428571 6.920260906219482 0.7420011467777131 0.8598130841121495 49.97108459472656 0.7605633802816901 0.627906976744186 0.9642857142857143 39.10533142089844 0.7690771274598031
5 3 -1 0.8785046728971962 0.7149893045425415 0.7941176470588236 0.675 0.9642857142857143 0.5805591344833374 0.7584630104317618 0.8878504672897196 139.26937866210938 0.793103448275862 0.7666666666666667 0.8214285714285714 142.61703491210938 0.7464071490241253 0.897196261682243 6.417535781860352 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.417535781860352 0.743486466982473 0.8598130841121495 50.244720458984375 0.7605633802816901 0.627906976744186 0.9642857142857143 39.23603057861328 0.7700890322217079
6 4 -1 0.8785046728971962 0.7147645950317383 0.7941176470588236 0.675 0.9642857142857143 0.581954836845398 0.7584630104317618 0.897196261682243 140.93128967285156 0.7999999999999999 0.8148148148148148 0.7857142857142857 140.93128967285156 0.746734202922608 0.897196261682243 6.424378871917725 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.424378871917725 0.7439523054917898 0.8598130841121495 50.70547866821289 0.7714285714285715 0.6428571428571429 0.9642857142857143 40.70288848876953 0.7732340939525525
7 5 -1 0.8785046728971962 0.7756680846214294 0.7941176470588236 0.675 0.9642857142857143 0.5837556719779968 0.7596923064980143 0.897196261682243 140.8372802734375 0.8070175438596492 0.7931034482758621 0.8214285714285714 141.61801147460938 0.7476783736943649 0.897196261682243 6.431297302246094 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.431297302246094 0.7439523054917898 0.8598130841121495 51.126739501953125 0.7714285714285715 0.6428571428571429 0.9642857142857143 40.991600036621094 0.7742007199191785
8 6 -1 0.8785046728971962 0.7758897542953491 0.7941176470588236 0.675 0.9642857142857143 0.5853708982467651 0.7596870261600728 0.897196261682243 140.56597900390625 0.8070175438596492 0.7931034482758621 0.8214285714285714 141.67572021484375 0.7482383537839616 0.897196261682243 6.416640281677246 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.416640281677246 0.7472146926888119 0.8598130841121495 53.09589767456055 0.7714285714285715 0.6428571428571429 0.9642857142857143 41.28678894042969 0.7718897142696635
9 7 -1 0.8785046728971962 0.7762866020202637 0.7941176470588236 0.675 0.9642857142857143 0.5878200531005859 0.7596870261600728 0.897196261682243 140.15020751953125 0.8070175438596492 0.7931034482758621 0.8214285714285714 141.2872314453125 0.7510123833437055 0.897196261682243 6.113794326782227 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.399294853210449 0.7495590150331343 0.8598130841121495 53.3231201171875 0.7714285714285715 0.6428571428571429 0.9642857142857143 41.694549560546875 0.7764593657594636
10 8 -1 0.8878504672897196 0.6951338052749634 0.7999999999999999 0.7027027027027027 0.9285714285714286 0.6463806629180908 0.761901030729765 0.897196261682243 139.57412719726562 0.8070175438596492 0.7931034482758621 0.8214285714285714 140.79031372070312 0.7522028595341816 0.897196261682243 6.1220855712890625 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.377052307128906 0.7518712111606615 0.8598130841121495 53.603271484375 0.7714285714285715 0.6428571428571429 0.9642857142857143 42.17536163330078 0.7778469140220119
11 9 -1 0.8878504672897196 0.697858452796936 0.8059701492537313 0.6923076923076923 0.9642857142857143 0.6171824336051941 0.7629305664756872 0.897196261682243 135.81292724609375 0.8070175438596492 0.7931034482758621 0.8214285714285714 140.23594665527344 0.7548442564499593 0.897196261682243 6.1298041343688965 0.7999999999999999 0.8148148148148148 0.7857142857142857 6.352500915527344 0.7539231117088027 0.8598130841121495 53.983299255371094 0.782608695652174 0.6585365853658537 0.9642857142857143 43.110023498535156 0.7775448251460915