Training in progress, epoch 4

eval/Information-Retrieval_evaluation_dim_128_results.csv

@@ -2,3 +2,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 1.0,1,0.125,0.375,0.375,0.75,0.125,0.125,0.125,0.375,0.07500000000000001,0.375,0.07500000000000001,0.75,0.2787698412698413,0.38732830198776314,0.29811507936507936
 2.0,2,0.125,0.375,0.375,0.875,0.125,0.125,0.125,0.375,0.07500000000000001,0.375,0.08750000000000001,0.875,0.28903769841269844,0.42122784820904857,0.298653083028083
 3.0,3,0.0,0.375,0.375,0.75,0.0,0.0,0.125,0.375,0.07500000000000001,0.375,0.07500000000000001,0.75,0.1994047619047619,0.3288662191964322,0.21943681318681318
+4.0,4,0.125,0.375,0.375,0.875,0.125,0.125,0.125,0.375,0.07500000000000001,0.375,0.08750000000000001,0.875,0.2926587301587301,0.4249570514457608,0.30227411477411475

eval/Information-Retrieval_evaluation_dim_256_results.csv

@@ -2,3 +2,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 1.0,1,0.0,0.25,0.375,0.625,0.0,0.0,0.08333333333333333,0.25,0.07500000000000001,0.375,0.0625,0.625,0.13645833333333332,0.24892281379226977,0.1662202380952381
 2.0,2,0.0,0.375,0.375,0.625,0.0,0.0,0.125,0.375,0.07500000000000001,0.375,0.0625,0.625,0.18154761904761904,0.2871995525297655,0.21279761904761904
 3.0,3,0.0,0.375,0.375,0.625,0.0,0.0,0.125,0.375,0.07500000000000001,0.375,0.0625,0.625,0.20238095238095238,0.3035657717261977,0.23363095238095238
+4.0,4,0.0,0.375,0.375,0.875,0.0,0.0,0.125,0.375,0.07500000000000001,0.375,0.08750000000000001,0.875,0.22738095238095235,0.37583197830566967,0.23779761904761904

eval/Information-Retrieval_evaluation_dim_512_results.csv

@@ -2,3 +2,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 1.0,1,0.25,0.25,0.375,0.875,0.25,0.25,0.08333333333333333,0.25,0.07500000000000001,0.375,0.08750000000000001,0.875,0.345436507936508,0.46384458208415147,0.3558531746031746
 2.0,2,0.125,0.375,0.375,0.875,0.125,0.125,0.125,0.375,0.07500000000000001,0.375,0.08750000000000001,0.875,0.29563492063492064,0.4278162831675969,0.3052503052503053
 3.0,3,0.0,0.375,0.5,0.75,0.0,0.0,0.125,0.375,0.1,0.5,0.07500000000000001,0.75,0.20882936507936506,0.3369962050802706,0.22757936507936508
+4.0,4,0.0,0.375,0.5,0.875,0.0,0.0,0.125,0.375,0.1,0.5,0.08750000000000001,0.875,0.22132936507936507,0.37312930837000663,0.2296626984126984

eval/Information-Retrieval_evaluation_dim_64_results.csv

@@ -2,3 +2,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 1.0,1,0.0,0.25,0.25,0.625,0.0,0.0,0.08333333333333333,0.25,0.05,0.25,0.0625,0.625,0.15833333333333335,0.2665511192631737,0.18878205128205128
 2.0,2,0.125,0.375,0.5,0.625,0.125,0.125,0.125,0.375,0.1,0.5,0.0625,0.625,0.2520833333333333,0.3399676730489101,0.2818452380952381
 3.0,3,0.25,0.375,0.375,0.875,0.25,0.25,0.125,0.375,0.07500000000000001,0.375,0.08750000000000001,0.875,0.35535714285714287,0.4709587716346414,0.3667207792207793
+4.0,4,0.0,0.375,0.5,0.625,0.0,0.0,0.125,0.375,0.1,0.5,0.0625,0.625,0.2157738095238095,0.3157336748187052,0.24797077922077923

eval/Information-Retrieval_evaluation_dim_768_results.csv

@@ -2,3 +2,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 1.0,1,0.0,0.25,0.375,0.875,0.0,0.0,0.08333333333333333,0.25,0.07500000000000001,0.375,0.08750000000000001,0.875,0.17876984126984125,0.33884458208415147,0.1871031746031746
 2.0,2,0.125,0.375,0.375,0.875,0.125,0.125,0.125,0.375,0.07500000000000001,0.375,0.08750000000000001,0.875,0.322172619047619,0.45002477971291655,0.32998511904761907
 3.0,3,0.0,0.375,0.5,0.875,0.0,0.0,0.125,0.375,0.1,0.5,0.08750000000000001,0.875,0.24523809523809523,0.39358903929718203,0.2521825396825397
+4.0,4,0.0,0.375,0.5,0.875,0.0,0.0,0.125,0.375,0.1,0.5,0.08750000000000001,0.875,0.21646825396825395,0.36914698568341187,0.2234126984126984