Training in progress, step 3375

Information-Retrieval_evaluation_BeIR-touche2020-subset-test_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.7755102040816326,0.9795918367346939,1.0,1.0,0.7755102040816326,0.017089566838806178,0.7414965986394557,0.04913135456425962,0.6734693877551022,0.0744729216014395,0.6061224489795918,0.13390399153802923,0.8792517006802721,0.6452010725749343,0.26987146167670506
 -1,-1,0.2653061224489796,0.5714285714285714,0.6938775510204082,0.7551020408163265,0.2653061224489796,0.005859789020652119,0.3469387755102041,0.022771209086251597,0.4,0.04397085795258936,0.3755102040816327,0.08239494960074849,0.42636054421768715,0.36314214650584564,0.16579582237011886
 -1,-1,0.7755102040816326,0.9795918367346939,1.0,1.0,0.7755102040816326,0.01706832759711131,0.7482993197278911,0.049401730544661945,0.7142857142857143,0.07867619617707583,0.6122448979591837,0.1349240729674531,0.8714285714285713,0.653970278908209,0.2786997022824942
+-1,-1,0.7551020408163265,0.9387755102040817,0.9591836734693877,1.0,0.7551020408163265,0.01662880113717669,0.7210884353741496,0.04763575042744458,0.6612244897959183,0.07282683231615908,0.5591836734693877,0.12302205261034137,0.8510689990281828,0.6039860530659029,0.24094937083231965

Information-Retrieval_evaluation_NanoArguAna_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.18,0.36,0.5,0.68,0.18,0.18,0.11999999999999998,0.36,0.10000000000000002,0.5,0.068,0.68,0.3243809523809524,0.4088546835300411,0.3354654705346437
 -1,-1,0.16,0.5,0.68,0.88,0.16,0.16,0.16666666666666663,0.5,0.136,0.68,0.088,0.88,0.3908412698412698,0.5077064028450745,0.3975778004159583
 -1,-1,0.16,0.42,0.56,0.8,0.16,0.16,0.13999999999999999,0.42,0.11200000000000003,0.56,0.08,0.8,0.346095238095238,0.4541392479306418,0.3511114131364851
+-1,-1,0.2,0.36,0.48,0.64,0.2,0.2,0.11999999999999998,0.36,0.09600000000000002,0.48,0.06400000000000002,0.64,0.3259920634920635,0.399971817141543,0.33708074446236025

Information-Retrieval_evaluation_NanoClimateFEVER_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.2,0.44,0.5,0.6,0.2,0.09666666666666666,0.14666666666666664,0.21566666666666662,0.10400000000000001,0.244,0.066,0.304,0.32441269841269843,0.23875559115390693,0.18002326993925138
 -1,-1,0.12,0.24,0.26,0.3,0.12,0.05833333333333333,0.08,0.11166666666666664,0.06000000000000001,0.13333333333333333,0.042,0.1733333333333333,0.18599999999999997,0.1421323657809101,0.11251502558321347
 -1,-1,0.22,0.52,0.56,0.64,0.22,0.09166666666666666,0.1733333333333333,0.23399999999999999,0.12000000000000002,0.27899999999999997,0.076,0.32733333333333337,0.3648571428571428,0.26355221051084216,0.19506453252604283
+-1,-1,0.22,0.32,0.42,0.54,0.22,0.10233333333333333,0.11333333333333333,0.17233333333333334,0.08800000000000001,0.214,0.06,0.264,0.2971587301587302,0.2160448650908654,0.16726239030401754

Information-Retrieval_evaluation_NanoDBPedia_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.72,0.78,0.82,0.92,0.72,0.07890647927098722,0.49333333333333335,0.1444097476150978,0.4320000000000001,0.17161496480028293,0.36199999999999993,0.24571882117909583,0.7622698412698413,0.47189065029725746,0.3083301597708803
 -1,-1,0.62,0.74,0.82,0.88,0.62,0.05294717669991995,0.4600000000000001,0.11950308612173167,0.40399999999999997,0.1809061480074522,0.352,0.26388938838721027,0.7002698412698414,0.45186572825718035,0.2963971880776791
 -1,-1,0.66,0.8,0.84,0.94,0.66,0.07082671665308901,0.5066666666666666,0.13730927885289243,0.4160000000000001,0.1661893911919123,0.368,0.25034697924131,0.7467142857142857,0.4728916713272679,0.30396194965649254
+-1,-1,0.52,0.8,0.84,0.94,0.52,0.053947284988985926,0.4733333333333334,0.12872420563450496,0.4,0.1614012024961392,0.33399999999999996,0.22961144710899753,0.658079365079365,0.4215257975939991,0.25522727699994674

Information-Retrieval_evaluation_NanoFEVER_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.48,0.7,0.84,0.92,0.48,0.42666666666666664,0.23333333333333336,0.6466666666666666,0.17199999999999996,0.7966666666666667,0.09399999999999999,0.8666666666666667,0.6137777777777778,0.647832874607183,0.568931348337861
 -1,-1,0.28,0.42,0.44,0.44,0.28,0.27,0.13999999999999999,0.4,0.09200000000000001,0.43,0.046000000000000006,0.43,0.3506666666666666,0.3661113939532885,0.3422393215160618
 -1,-1,0.6,0.9,0.96,0.98,0.6,0.5566666666666666,0.30666666666666664,0.8466666666666667,0.19599999999999995,0.9066666666666667,0.09999999999999998,0.9266666666666667,0.7516666666666666,0.7716934881014161,0.7061067287383075
+-1,-1,0.4,0.66,0.74,0.86,0.4,0.37666666666666665,0.22666666666666668,0.6133333333333333,0.156,0.6933333333333332,0.09,0.8133333333333332,0.551190476190476,0.60296133344697,0.5334152795270443

Information-Retrieval_evaluation_NanoFiQA2018_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.34,0.42,0.52,0.6,0.34,0.17874603174603174,0.1733333333333333,0.26026984126984126,0.14400000000000002,0.3431031746031746,0.092,0.44262698412698415,0.4107380952380952,0.3483765709350854,0.2899028574096885
 -1,-1,0.16,0.32,0.36,0.42,0.16,0.09666666666666666,0.11333333333333333,0.2333333333333333,0.07600000000000001,0.24833333333333332,0.05000000000000001,0.2977777777777778,0.23633333333333328,0.21754856447960677,0.18156772343708624
 -1,-1,0.36,0.48,0.6,0.66,0.36,0.19941269841269843,0.20666666666666667,0.2806031746031746,0.16,0.3781269841269841,0.08999999999999998,0.4256269841269841,0.4481666666666666,0.35641512120073343,0.29847071848639917
+-1,-1,0.26,0.4,0.54,0.6,0.26,0.16085714285714287,0.14666666666666667,0.23674603174603173,0.124,0.32276984126984126,0.07400000000000001,0.4006269841269841,0.36907936507936495,0.30934647962611306,0.2520414233453418

Information-Retrieval_evaluation_NanoHotpotQA_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.66,0.8,0.82,0.9,0.66,0.33,0.3066666666666667,0.46,0.18799999999999997,0.47,0.11399999999999999,0.57,0.7386111111111111,0.5429476399940535,0.44804908578281555
 -1,-1,0.46,0.6,0.66,0.78,0.46,0.23,0.26,0.39,0.176,0.44,0.10399999999999998,0.52,0.5547222222222222,0.45661766676516835,0.389670298499331
 -1,-1,0.74,0.82,0.84,0.86,0.74,0.37,0.33333333333333326,0.5,0.21599999999999997,0.54,0.12399999999999999,0.62,0.7883333333333334,0.6038529756799117,0.5248449945769594
+-1,-1,0.52,0.62,0.64,0.68,0.52,0.26,0.23333333333333336,0.35,0.14800000000000002,0.37,0.08,0.4,0.5784999999999999,0.4083907397898535,0.34877240523636466

Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.32,0.54,0.64,0.72,0.32,0.32,0.18,0.54,0.12800000000000003,0.64,0.07200000000000001,0.72,0.4551666666666666,0.5194788229083886,0.46866687154926134
 -1,-1,0.46,0.64,0.78,0.84,0.46,0.46,0.21333333333333332,0.64,0.156,0.78,0.08399999999999999,0.84,0.5809365079365079,0.6436072717719088,0.5875442422678194
 -1,-1,0.34,0.6,0.66,0.7,0.34,0.34,0.2,0.6,0.132,0.66,0.07,0.7,0.4747460317460317,0.5303422656736582,0.48845125969077435
+-1,-1,0.3,0.5,0.58,0.7,0.3,0.3,0.16666666666666669,0.5,0.11599999999999999,0.58,0.07,0.7,0.4282222222222222,0.49319518919591504,0.44089915437302396

Information-Retrieval_evaluation_NanoNFCorpus_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.32,0.38,0.5,0.56,0.32,0.010995012876071315,0.28,0.02828544592719776,0.27199999999999996,0.06650305246570268,0.23000000000000004,0.08873790175812095,0.3792698412698413,0.25433221795160377,0.09691975523503352
 -1,-1,0.38,0.48,0.56,0.7,0.38,0.01687245746538031,0.33333333333333326,0.04124468301356519,0.32,0.06123009468323657,0.278,0.10651046552028522,0.4581269841269841,0.304412503772871,0.1278020171916061
 -1,-1,0.36,0.48,0.5,0.64,0.36,0.011117260803746984,0.3133333333333333,0.052618880243359395,0.29200000000000004,0.07334367009403865,0.26199999999999996,0.11778483188857766,0.43522222222222234,0.2943241147857984,0.121057858108288
+-1,-1,0.36,0.48,0.5,0.62,0.36,0.012173359206591558,0.3,0.028722229702908417,0.284,0.04538392607412603,0.23399999999999999,0.0669521595133137,0.43173809523809525,0.2590743459873399,0.08094835917197184

Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4,0.58,0.6,0.7,0.4,0.36,0.20666666666666664,0.56,0.128,0.58,0.07400000000000001,0.67,0.5013888888888889,0.5294958669542686,0.48856950315109743
 -1,-1,0.42,0.58,0.66,0.76,0.42,0.38,0.19333333333333333,0.54,0.136,0.62,0.08399999999999999,0.74,0.5124126984126984,0.5512960895859668,0.4936325526558866
 -1,-1,0.44,0.56,0.64,0.74,0.44,0.41,0.19333333333333333,0.53,0.132,0.61,0.078,0.7,0.523047619047619,0.5519763173860046,0.5093692007660835
+-1,-1,0.26,0.38,0.48,0.54,0.26,0.23,0.13333333333333333,0.35,0.1,0.45,0.05600000000000001,0.51,0.34907936507936504,0.3731343310366586,0.33487673362538833

Information-Retrieval_evaluation_NanoQuoraRetrieval_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.88,0.94,0.96,0.98,0.88,0.7573333333333333,0.38666666666666655,0.902,0.25199999999999995,0.9393333333333334,0.13399999999999998,0.9733333333333334,0.9111904761904762,0.9171619661571674,0.8950605680868838
 -1,-1,0.48,0.56,0.62,0.66,0.48,0.44666666666666666,0.21333333333333335,0.514,0.14400000000000002,0.5673333333333334,0.08199999999999999,0.6213333333333333,0.539079365079365,0.5489572541869099,0.5287672335161302
 -1,-1,0.8,0.94,0.94,0.96,0.8,0.6973333333333332,0.4,0.9086666666666667,0.25199999999999995,0.9259999999999999,0.12799999999999997,0.946,0.8655555555555554,0.8793556978310312,0.8572134707397865
+-1,-1,0.8,0.9,0.92,0.96,0.8,0.7006666666666667,0.3733333333333333,0.862,0.23199999999999996,0.8886666666666667,0.12799999999999997,0.946,0.8575,0.8709345901262452,0.8417246177735308

Information-Retrieval_evaluation_NanoSCIDOCS_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.46,0.7,0.74,0.8,0.46,0.09666666666666668,0.33333333333333326,0.20666666666666664,0.276,0.2826666666666667,0.18599999999999997,0.38166666666666665,0.5806666666666667,0.3746688514609652,0.2919508397066463
 -1,-1,0.46,0.6,0.66,0.76,0.46,0.09666666666666668,0.31333333333333335,0.19266666666666665,0.264,0.26866666666666666,0.16799999999999998,0.3436666666666666,0.5551904761904762,0.3502034656888579,0.28238523085822703
 -1,-1,0.44,0.68,0.72,0.88,0.44,0.09266666666666667,0.3533333333333333,0.21666666666666667,0.28,0.2856666666666667,0.19399999999999995,0.39666666666666656,0.5817936507936508,0.3839901352188253,0.29483854671038273
+-1,-1,0.44,0.62,0.7,0.8,0.44,0.09,0.2866666666666667,0.175,0.21999999999999997,0.22399999999999998,0.16400000000000003,0.3356666666666667,0.5561031746031745,0.32838811799960327,0.24434998843859707

Information-Retrieval_evaluation_NanoSciFact_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.4,0.52,0.58,0.68,0.4,0.355,0.19333333333333333,0.495,0.136,0.57,0.08,0.68,0.4829365079365079,0.5213214878209026,0.47407253898671803
 -1,-1,0.38,0.46,0.54,0.56,0.38,0.345,0.15999999999999998,0.43,0.12399999999999999,0.52,0.064,0.54,0.4325555555555555,0.4484758215930127,0.42353656705038156
 -1,-1,0.46,0.54,0.64,0.74,0.46,0.415,0.2,0.52,0.14400000000000002,0.625,0.08599999999999998,0.74,0.5398333333333334,0.5798929270624772,0.5303142135642136
+-1,-1,0.3,0.5,0.52,0.62,0.3,0.265,0.1733333333333333,0.46,0.11600000000000002,0.495,0.07,0.6,0.4002698412698413,0.43558334687061145,0.3861669168464833

Information-Retrieval_evaluation_NanoTouche2020_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.673469387755102,0.8367346938775511,0.8979591836734694,0.9795918367346939,0.673469387755102,0.046731422569131785,0.5578231292517006,0.12234845881617477,0.5142857142857143,0.18500594654519,0.40816326530612246,0.27622055850807264,0.7676546809199871,0.48003101771257267,0.3564545575416437
 -1,-1,0.30612244897959184,0.5714285714285714,0.6938775510204082,0.7755102040816326,0.30612244897959184,0.024834233991487722,0.346938775510204,0.08169446144223932,0.33469387755102037,0.12462402887314433,0.2755102040816326,0.19542890091501577,0.4607142857142857,0.3078492074305264,0.25713131957408375
 -1,-1,0.6530612244897959,0.7755102040816326,0.8571428571428571,0.9387755102040817,0.6530612244897959,0.04497799044877029,0.5374149659863945,0.11546047315036259,0.5020408163265306,0.18376483178712996,0.4040816326530612,0.2772240574916768,0.7406705539358601,0.4711126371779877,0.35552822693119057
+-1,-1,0.6326530612244898,0.8163265306122449,0.8979591836734694,0.9591836734693877,0.6326530612244898,0.04499413135420742,0.4965986394557823,0.1065943935391371,0.46938775510204084,0.16649967473172042,0.37142857142857144,0.24826882087723884,0.7421768707482992,0.43458124412524113,0.31599660374216376

NanoBEIR_evaluation_mean_results.csv

@@ -21,3 +21,4 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 -1,-1,0.46411302982731556,0.6151334379905808,0.6859968602825746,0.772276295133438,0.46411302982731556,0.24905479075350428,0.27778126635269496,0.3801010379714086,0.21894505494505495,0.4452995234677705,0.15232025117739403,0.5306900717106877,0.5578818619022701,0.4811652493448767,0.40018437123326334
 -1,-1,0.3604709576138147,0.5162637362637362,0.5949136577708006,0.6735007849293564,0.3604709576138147,0.202922092422317,0.23027734170591313,0.3226237613264772,0.18636106750392464,0.388802072171577,0.13211616954474098,0.45784152814874024,0.45829609279609274,0.4074449027777909,0.34005896312642037
 -1,-1,0.4794662480376766,0.6550392464678179,0.7167032967032967,0.8060596546310832,0.4794662480376766,0.26612830766551065,0.29723704866562006,0.41246090821921455,0.22723390894819467,0.4764429392718,0.1584678178963893,0.5559730399550165,0.5851309461513544,0.5087337546066613,0.42587177797164666
+-1,-1,0.40097331240188383,0.5658712715855574,0.6352276295133438,0.7276295133437991,0.40097331240188383,0.21512604500566113,0.24948194662480377,0.33411180979148064,0.19610675039246467,0.39161958804398667,0.1381098901098901,0.4734199547405025,0.5034684283969997,0.4271640152331507,0.3491355302958642

config.json

@@ -15,7 +15,7 @@
   "max_position_embeddings": 512,
   "model_type": "bert",
   "num_attention_heads": 12,
-  "num_hidden_layers": 6,
+  "num_hidden_layers": 12,
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "transformers_version": "4.57.3",

eval/Information-Retrieval_evaluation_NanoMSMARCO_results.csv

@@ -249,3 +249,17 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 5.172413793103448,4500,0.3,0.5,0.58,0.68,0.3,0.3,0.16666666666666663,0.5,0.11599999999999999,0.58,0.068,0.68,0.42316666666666664,0.48508399522056306,0.4372737798319072
 5.459770114942529,4750,0.28,0.5,0.58,0.7,0.28,0.28,0.16666666666666669,0.5,0.11599999999999999,0.58,0.07,0.7,0.41788888888888887,0.48552693907025524,0.430681710021151
 5.747126436781609,5000,0.3,0.5,0.58,0.68,0.3,0.3,0.16666666666666669,0.5,0.11599999999999999,0.58,0.068,0.68,0.4262222222222222,0.48741389266955737,0.44072094685707097
+0,0,0.38,0.62,0.68,0.8,0.38,0.38,0.20666666666666667,0.62,0.136,0.68,0.08,0.8,0.5215238095238095,0.5887227948760404,0.5325402082997991
+0.28735632183908044,250,0.32,0.56,0.68,0.76,0.32,0.32,0.18666666666666668,0.56,0.136,0.68,0.07600000000000001,0.76,0.46605555555555545,0.5369779802620738,0.475537637537946
+0.5747126436781609,500,0.36,0.56,0.62,0.7,0.36,0.36,0.18666666666666668,0.56,0.124,0.62,0.07,0.7,0.46619047619047604,0.5222471770724489,0.4783974452787037
+0.8620689655172413,750,0.38,0.5,0.66,0.72,0.38,0.38,0.16666666666666663,0.5,0.132,0.66,0.07200000000000001,0.72,0.4767460317460317,0.5348116648156811,0.4882227707014616
+1.1494252873563218,1000,0.34,0.52,0.62,0.7,0.34,0.34,0.1733333333333333,0.52,0.124,0.62,0.07,0.7,0.4593015873015872,0.5172190015638278,0.4728120551145889
+1.4367816091954024,1250,0.32,0.56,0.62,0.72,0.32,0.32,0.18666666666666668,0.56,0.124,0.62,0.07200000000000001,0.72,0.46071428571428563,0.523636511509153,0.47376044282369584
+1.7241379310344827,1500,0.36,0.52,0.62,0.74,0.36,0.36,0.1733333333333333,0.52,0.124,0.62,0.07400000000000001,0.74,0.4669444444444444,0.5311580700909918,0.4793979165440129
+2.0114942528735633,1750,0.36,0.6,0.66,0.72,0.36,0.36,0.2,0.6,0.132,0.66,0.07200000000000001,0.72,0.49085714285714277,0.5467607338298711,0.5010982382114398
+2.2988505747126435,2000,0.3,0.56,0.62,0.72,0.3,0.3,0.18666666666666668,0.56,0.124,0.62,0.07200000000000001,0.72,0.43607142857142855,0.504508403012926,0.4471925376562265
+2.586206896551724,2250,0.34,0.54,0.66,0.68,0.34,0.34,0.18,0.54,0.132,0.66,0.068,0.68,0.45752380952380944,0.5123064740304947,0.47135912772723587
+2.873563218390805,2500,0.38,0.54,0.66,0.72,0.38,0.38,0.18,0.54,0.132,0.66,0.07200000000000001,0.72,0.4893888888888888,0.5450938485549827,0.5005963492091311
+3.160919540229885,2750,0.34,0.54,0.62,0.68,0.34,0.34,0.18,0.54,0.124,0.62,0.068,0.68,0.4507460317460317,0.5064820353083469,0.46424148304277113
+3.4482758620689653,3000,0.38,0.54,0.62,0.7,0.38,0.38,0.18,0.54,0.124,0.62,0.07,0.7,0.47494444444444445,0.5286501960024682,0.4876936286321665
+3.735632183908046,3250,0.36,0.58,0.62,0.7,0.36,0.36,0.19333333333333333,0.58,0.124,0.62,0.07,0.7,0.47507936507936505,0.5293969846378502,0.4876720668963073

eval/Information-Retrieval_evaluation_NanoNQ_results.csv

@@ -249,3 +249,17 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 5.172413793103448,4500,0.26,0.4,0.48,0.54,0.26,0.23,0.14,0.37,0.1,0.45,0.05600000000000001,0.51,0.3501666666666667,0.37493713821170965,0.3375598268411981
 5.459770114942529,4750,0.24,0.42,0.48,0.54,0.24,0.21,0.14666666666666667,0.39,0.1,0.45,0.05600000000000001,0.51,0.3455238095238095,0.3725107396866955,0.3342746615754654
 5.747126436781609,5000,0.26,0.4,0.48,0.54,0.26,0.23,0.14,0.37,0.1,0.45,0.05600000000000001,0.51,0.35074603174603175,0.3745207998751907,0.3364191132763434
+0,0,0.44,0.62,0.7,0.72,0.44,0.42,0.20666666666666664,0.59,0.15200000000000002,0.69,0.07800000000000001,0.71,0.5425,0.5785694545006416,0.5396412232598975
+0.28735632183908044,250,0.46,0.54,0.56,0.62,0.46,0.43,0.19333333333333333,0.52,0.12,0.54,0.068,0.61,0.5126666666666666,0.5294909534420024,0.5153920890604266
+0.5747126436781609,500,0.44,0.54,0.56,0.68,0.44,0.41,0.19333333333333333,0.52,0.12,0.54,0.07400000000000001,0.66,0.5087460317460318,0.5367437892501795,0.502667434475417
+0.8620689655172413,750,0.4,0.52,0.58,0.74,0.4,0.36,0.18,0.49,0.124,0.56,0.078,0.7,0.4850555555555555,0.5194468955652417,0.4631364820423963
+1.1494252873563218,1000,0.34,0.6,0.64,0.72,0.34,0.32,0.20666666666666664,0.57,0.136,0.62,0.07600000000000001,0.69,0.4690555555555555,0.5147756596366279,0.4626675175963833
+1.4367816091954024,1250,0.36,0.5,0.54,0.66,0.36,0.33,0.18,0.48,0.11600000000000002,0.52,0.07,0.63,0.4454682539682539,0.47942547035330213,0.43986954184399624
+1.7241379310344827,1500,0.38,0.56,0.56,0.7,0.38,0.35,0.2,0.54,0.12,0.54,0.07400000000000001,0.67,0.47538888888888897,0.5116929483335023,0.4677392938232293
+2.0114942528735633,1750,0.36,0.52,0.62,0.66,0.36,0.34,0.18,0.5,0.132,0.6,0.07200000000000001,0.64,0.46005555555555555,0.49847115918125295,0.4587203669439037
+2.2988505747126435,2000,0.36,0.54,0.56,0.66,0.36,0.33,0.18,0.5,0.11599999999999999,0.53,0.07,0.63,0.4607698412698413,0.48668089533311,0.4447607166718558
+2.586206896551724,2250,0.32,0.54,0.58,0.66,0.32,0.31,0.18666666666666665,0.51,0.124,0.56,0.07,0.63,0.439579365079365,0.48001967818554603,0.4393154782211029
+2.873563218390805,2500,0.4,0.56,0.58,0.72,0.4,0.36,0.19333333333333333,0.53,0.12,0.55,0.07600000000000001,0.69,0.4952460317460317,0.5258620738671133,0.4760610127303948
+3.160919540229885,2750,0.42,0.54,0.56,0.72,0.42,0.39,0.19333333333333333,0.52,0.12,0.54,0.07600000000000001,0.69,0.5023809523809523,0.5345738454365045,0.49005173651629347
+3.4482758620689653,3000,0.36,0.54,0.58,0.72,0.36,0.34,0.18,0.5,0.12,0.55,0.07400000000000001,0.68,0.4706031746031746,0.5066247160418815,0.4544901931357376
+3.735632183908046,3250,0.4,0.56,0.58,0.74,0.4,0.37,0.19333333333333333,0.53,0.12,0.55,0.07600000000000001,0.7,0.49621428571428566,0.5283136453383426,0.47570813068007134

eval/NanoBEIR_evaluation_mean_results.csv

@@ -249,3 +249,17 @@ epoch,steps,cosine-Accuracy@1,cosine-Accuracy@3,cosine-Accuracy@5,cosine-Accurac
 5.172413793103448,4500,0.28,0.45,0.53,0.6100000000000001,0.28,0.265,0.15333333333333332,0.435,0.108,0.515,0.062000000000000006,0.595,0.38666666666666666,0.43001056671613636,0.38741680333655265
 5.459770114942529,4750,0.26,0.45999999999999996,0.53,0.62,0.26,0.245,0.15666666666666668,0.445,0.108,0.515,0.063,0.605,0.38170634920634916,0.4290188393784754,0.3824781857983082
 5.747126436781609,5000,0.28,0.45,0.53,0.6100000000000001,0.28,0.265,0.15333333333333335,0.435,0.108,0.515,0.062000000000000006,0.595,0.388484126984127,0.43096734627237404,0.3885700300667072
+0,0,0.41000000000000003,0.62,0.69,0.76,0.41000000000000003,0.4,0.20666666666666667,0.605,0.14400000000000002,0.685,0.07900000000000001,0.755,0.5320119047619047,0.583646124688341,0.5360907157798482
+0.28735632183908044,250,0.39,0.55,0.6200000000000001,0.69,0.39,0.375,0.19,0.54,0.128,0.6100000000000001,0.07200000000000001,0.685,0.489361111111111,0.5332344668520381,0.49546486329918626
+0.5747126436781609,500,0.4,0.55,0.5900000000000001,0.69,0.4,0.385,0.19,0.54,0.122,0.5800000000000001,0.07200000000000001,0.6799999999999999,0.48746825396825394,0.5294954831613142,0.4905324398770603
+0.8620689655172413,750,0.39,0.51,0.62,0.73,0.39,0.37,0.1733333333333333,0.495,0.128,0.6100000000000001,0.07500000000000001,0.71,0.48090079365079363,0.5271292801904615,0.47567962637192895
+1.1494252873563218,1000,0.34,0.56,0.63,0.71,0.34,0.33,0.18999999999999997,0.5449999999999999,0.13,0.62,0.07300000000000001,0.695,0.46417857142857133,0.5159973306002279,0.4677397863554861
+1.4367816091954024,1250,0.33999999999999997,0.53,0.5800000000000001,0.69,0.33999999999999997,0.325,0.18333333333333335,0.52,0.12000000000000001,0.5700000000000001,0.07100000000000001,0.675,0.4530912698412698,0.5015309909312275,0.45681499233384604
+1.7241379310344827,1500,0.37,0.54,0.5900000000000001,0.72,0.37,0.355,0.18666666666666665,0.53,0.122,0.5800000000000001,0.07400000000000001,0.7050000000000001,0.4711666666666667,0.5214255092122471,0.4735686051836211
+2.0114942528735633,1750,0.36,0.56,0.64,0.69,0.36,0.35,0.19,0.55,0.132,0.63,0.07200000000000001,0.6799999999999999,0.47545634920634916,0.522615946505562,0.4799093025776718
+2.2988505747126435,2000,0.32999999999999996,0.55,0.5900000000000001,0.69,0.32999999999999996,0.315,0.18333333333333335,0.53,0.12,0.575,0.07100000000000001,0.675,0.4484206349206349,0.495594649173018,0.4459766271640412
+2.586206896551724,2250,0.33,0.54,0.62,0.67,0.33,0.325,0.18333333333333332,0.525,0.128,0.6100000000000001,0.069,0.655,0.44855158730158723,0.49616307610802035,0.4553373029741694
+2.873563218390805,2500,0.39,0.55,0.62,0.72,0.39,0.37,0.18666666666666665,0.535,0.126,0.605,0.07400000000000001,0.705,0.49231746031746026,0.535477961211048,0.48832868096976295
+3.160919540229885,2750,0.38,0.54,0.5900000000000001,0.7,0.38,0.365,0.18666666666666665,0.53,0.122,0.5800000000000001,0.07200000000000001,0.685,0.47656349206349197,0.5205279403724257,0.47714660977953227
+3.4482758620689653,3000,0.37,0.54,0.6,0.71,0.37,0.36,0.18,0.52,0.122,0.585,0.07200000000000001,0.69,0.47277380952380954,0.5176374560221748,0.471091910883952
+3.735632183908046,3250,0.38,0.5700000000000001,0.6,0.72,0.38,0.365,0.19333333333333333,0.5549999999999999,0.122,0.585,0.07300000000000001,0.7,0.48564682539682535,0.5288553149880963,0.48169009878818936

final_metrics.json

@@ -1,231 +1,231 @@
 {
   "nano_beir": {
     "NanoClimateFEVER_cosine_accuracy@1": 0.22,
-    "NanoClimateFEVER_cosine_accuracy@3": 0.52,
-    "NanoClimateFEVER_cosine_accuracy@5": 0.56,
-    "NanoClimateFEVER_cosine_accuracy@10": 0.64,
+    "NanoClimateFEVER_cosine_accuracy@3": 0.32,
+    "NanoClimateFEVER_cosine_accuracy@5": 0.42,
+    "NanoClimateFEVER_cosine_accuracy@10": 0.54,
     "NanoClimateFEVER_cosine_precision@1": 0.22,
-    "NanoClimateFEVER_cosine_precision@3": 0.1733333333333333,
-    "NanoClimateFEVER_cosine_precision@5": 0.12000000000000002,
-    "NanoClimateFEVER_cosine_precision@10": 0.076,
-    "NanoClimateFEVER_cosine_recall@1": 0.09166666666666666,
-    "NanoClimateFEVER_cosine_recall@3": 0.23399999999999999,
-    "NanoClimateFEVER_cosine_recall@5": 0.27899999999999997,
-    "NanoClimateFEVER_cosine_recall@10": 0.32733333333333337,
-    "NanoClimateFEVER_cosine_ndcg@10": 0.26355221051084216,
-    "NanoClimateFEVER_cosine_mrr@10": 0.3648571428571428,
-    "NanoClimateFEVER_cosine_map@100": 0.19506453252604283,
-    "NanoDBPedia_cosine_accuracy@1": 0.66,
+    "NanoClimateFEVER_cosine_precision@3": 0.11333333333333333,
+    "NanoClimateFEVER_cosine_precision@5": 0.08800000000000001,
+    "NanoClimateFEVER_cosine_precision@10": 0.06,
+    "NanoClimateFEVER_cosine_recall@1": 0.10233333333333333,
+    "NanoClimateFEVER_cosine_recall@3": 0.17233333333333334,
+    "NanoClimateFEVER_cosine_recall@5": 0.214,
+    "NanoClimateFEVER_cosine_recall@10": 0.264,
+    "NanoClimateFEVER_cosine_ndcg@10": 0.2160448650908654,
+    "NanoClimateFEVER_cosine_mrr@10": 0.2971587301587302,
+    "NanoClimateFEVER_cosine_map@100": 0.16726239030401754,
+    "NanoDBPedia_cosine_accuracy@1": 0.52,
     "NanoDBPedia_cosine_accuracy@3": 0.8,
     "NanoDBPedia_cosine_accuracy@5": 0.84,
     "NanoDBPedia_cosine_accuracy@10": 0.94,
-    "NanoDBPedia_cosine_precision@1": 0.66,
-    "NanoDBPedia_cosine_precision@3": 0.5066666666666666,
-    "NanoDBPedia_cosine_precision@5": 0.4160000000000001,
-    "NanoDBPedia_cosine_precision@10": 0.368,
-    "NanoDBPedia_cosine_recall@1": 0.07082671665308901,
-    "NanoDBPedia_cosine_recall@3": 0.13730927885289243,
-    "NanoDBPedia_cosine_recall@5": 0.1661893911919123,
-    "NanoDBPedia_cosine_recall@10": 0.25034697924131,
-    "NanoDBPedia_cosine_ndcg@10": 0.4728916713272679,
-    "NanoDBPedia_cosine_mrr@10": 0.7467142857142857,
-    "NanoDBPedia_cosine_map@100": 0.30396194965649254,
-    "NanoFEVER_cosine_accuracy@1": 0.6,
-    "NanoFEVER_cosine_accuracy@3": 0.9,
-    "NanoFEVER_cosine_accuracy@5": 0.96,
-    "NanoFEVER_cosine_accuracy@10": 0.98,
-    "NanoFEVER_cosine_precision@1": 0.6,
-    "NanoFEVER_cosine_precision@3": 0.30666666666666664,
-    "NanoFEVER_cosine_precision@5": 0.19599999999999995,
-    "NanoFEVER_cosine_precision@10": 0.09999999999999998,
-    "NanoFEVER_cosine_recall@1": 0.5566666666666666,
-    "NanoFEVER_cosine_recall@3": 0.8466666666666667,
-    "NanoFEVER_cosine_recall@5": 0.9066666666666667,
-    "NanoFEVER_cosine_recall@10": 0.9266666666666667,
-    "NanoFEVER_cosine_ndcg@10": 0.7716934881014161,
-    "NanoFEVER_cosine_mrr@10": 0.7516666666666666,
-    "NanoFEVER_cosine_map@100": 0.7061067287383075,
-    "NanoFiQA2018_cosine_accuracy@1": 0.36,
-    "NanoFiQA2018_cosine_accuracy@3": 0.48,
-    "NanoFiQA2018_cosine_accuracy@5": 0.6,
-    "NanoFiQA2018_cosine_accuracy@10": 0.66,
-    "NanoFiQA2018_cosine_precision@1": 0.36,
-    "NanoFiQA2018_cosine_precision@3": 0.20666666666666667,
-    "NanoFiQA2018_cosine_precision@5": 0.16,
-    "NanoFiQA2018_cosine_precision@10": 0.08999999999999998,
-    "NanoFiQA2018_cosine_recall@1": 0.19941269841269843,
-    "NanoFiQA2018_cosine_recall@3": 0.2806031746031746,
-    "NanoFiQA2018_cosine_recall@5": 0.3781269841269841,
-    "NanoFiQA2018_cosine_recall@10": 0.4256269841269841,
-    "NanoFiQA2018_cosine_ndcg@10": 0.35641512120073343,
-    "NanoFiQA2018_cosine_mrr@10": 0.4481666666666666,
-    "NanoFiQA2018_cosine_map@100": 0.29847071848639917,
-    "NanoHotpotQA_cosine_accuracy@1": 0.74,
-    "NanoHotpotQA_cosine_accuracy@3": 0.82,
-    "NanoHotpotQA_cosine_accuracy@5": 0.84,
-    "NanoHotpotQA_cosine_accuracy@10": 0.86,
-    "NanoHotpotQA_cosine_precision@1": 0.74,
-    "NanoHotpotQA_cosine_precision@3": 0.33333333333333326,
-    "NanoHotpotQA_cosine_precision@5": 0.21599999999999997,
-    "NanoHotpotQA_cosine_precision@10": 0.12399999999999999,
-    "NanoHotpotQA_cosine_recall@1": 0.37,
-    "NanoHotpotQA_cosine_recall@3": 0.5,
-    "NanoHotpotQA_cosine_recall@5": 0.54,
-    "NanoHotpotQA_cosine_recall@10": 0.62,
-    "NanoHotpotQA_cosine_ndcg@10": 0.6038529756799117,
-    "NanoHotpotQA_cosine_mrr@10": 0.7883333333333334,
-    "NanoHotpotQA_cosine_map@100": 0.5248449945769594,
-    "NanoMSMARCO_cosine_accuracy@1": 0.34,
-    "NanoMSMARCO_cosine_accuracy@3": 0.6,
-    "NanoMSMARCO_cosine_accuracy@5": 0.66,
+    "NanoDBPedia_cosine_precision@1": 0.52,
+    "NanoDBPedia_cosine_precision@3": 0.4733333333333334,
+    "NanoDBPedia_cosine_precision@5": 0.4,
+    "NanoDBPedia_cosine_precision@10": 0.33399999999999996,
+    "NanoDBPedia_cosine_recall@1": 0.053947284988985926,
+    "NanoDBPedia_cosine_recall@3": 0.12872420563450496,
+    "NanoDBPedia_cosine_recall@5": 0.1614012024961392,
+    "NanoDBPedia_cosine_recall@10": 0.22961144710899753,
+    "NanoDBPedia_cosine_ndcg@10": 0.4215257975939991,
+    "NanoDBPedia_cosine_mrr@10": 0.658079365079365,
+    "NanoDBPedia_cosine_map@100": 0.25522727699994674,
+    "NanoFEVER_cosine_accuracy@1": 0.4,
+    "NanoFEVER_cosine_accuracy@3": 0.66,
+    "NanoFEVER_cosine_accuracy@5": 0.74,
+    "NanoFEVER_cosine_accuracy@10": 0.86,
+    "NanoFEVER_cosine_precision@1": 0.4,
+    "NanoFEVER_cosine_precision@3": 0.22666666666666668,
+    "NanoFEVER_cosine_precision@5": 0.156,
+    "NanoFEVER_cosine_precision@10": 0.09,
+    "NanoFEVER_cosine_recall@1": 0.37666666666666665,
+    "NanoFEVER_cosine_recall@3": 0.6133333333333333,
+    "NanoFEVER_cosine_recall@5": 0.6933333333333332,
+    "NanoFEVER_cosine_recall@10": 0.8133333333333332,
+    "NanoFEVER_cosine_ndcg@10": 0.60296133344697,
+    "NanoFEVER_cosine_mrr@10": 0.551190476190476,
+    "NanoFEVER_cosine_map@100": 0.5334152795270443,
+    "NanoFiQA2018_cosine_accuracy@1": 0.26,
+    "NanoFiQA2018_cosine_accuracy@3": 0.4,
+    "NanoFiQA2018_cosine_accuracy@5": 0.54,
+    "NanoFiQA2018_cosine_accuracy@10": 0.6,
+    "NanoFiQA2018_cosine_precision@1": 0.26,
+    "NanoFiQA2018_cosine_precision@3": 0.14666666666666667,
+    "NanoFiQA2018_cosine_precision@5": 0.124,
+    "NanoFiQA2018_cosine_precision@10": 0.07400000000000001,
+    "NanoFiQA2018_cosine_recall@1": 0.16085714285714287,
+    "NanoFiQA2018_cosine_recall@3": 0.23674603174603173,
+    "NanoFiQA2018_cosine_recall@5": 0.32276984126984126,
+    "NanoFiQA2018_cosine_recall@10": 0.4006269841269841,
+    "NanoFiQA2018_cosine_ndcg@10": 0.30934647962611306,
+    "NanoFiQA2018_cosine_mrr@10": 0.36907936507936495,
+    "NanoFiQA2018_cosine_map@100": 0.2520414233453418,
+    "NanoHotpotQA_cosine_accuracy@1": 0.52,
+    "NanoHotpotQA_cosine_accuracy@3": 0.62,
+    "NanoHotpotQA_cosine_accuracy@5": 0.64,
+    "NanoHotpotQA_cosine_accuracy@10": 0.68,
+    "NanoHotpotQA_cosine_precision@1": 0.52,
+    "NanoHotpotQA_cosine_precision@3": 0.23333333333333336,
+    "NanoHotpotQA_cosine_precision@5": 0.14800000000000002,
+    "NanoHotpotQA_cosine_precision@10": 0.08,
+    "NanoHotpotQA_cosine_recall@1": 0.26,
+    "NanoHotpotQA_cosine_recall@3": 0.35,
+    "NanoHotpotQA_cosine_recall@5": 0.37,
+    "NanoHotpotQA_cosine_recall@10": 0.4,
+    "NanoHotpotQA_cosine_ndcg@10": 0.4083907397898535,
+    "NanoHotpotQA_cosine_mrr@10": 0.5784999999999999,
+    "NanoHotpotQA_cosine_map@100": 0.34877240523636466,
+    "NanoMSMARCO_cosine_accuracy@1": 0.3,
+    "NanoMSMARCO_cosine_accuracy@3": 0.5,
+    "NanoMSMARCO_cosine_accuracy@5": 0.58,
     "NanoMSMARCO_cosine_accuracy@10": 0.7,
-    "NanoMSMARCO_cosine_precision@1": 0.34,
-    "NanoMSMARCO_cosine_precision@3": 0.2,
-    "NanoMSMARCO_cosine_precision@5": 0.132,
+    "NanoMSMARCO_cosine_precision@1": 0.3,
+    "NanoMSMARCO_cosine_precision@3": 0.16666666666666669,
+    "NanoMSMARCO_cosine_precision@5": 0.11599999999999999,
     "NanoMSMARCO_cosine_precision@10": 0.07,
-    "NanoMSMARCO_cosine_recall@1": 0.34,
-    "NanoMSMARCO_cosine_recall@3": 0.6,
-    "NanoMSMARCO_cosine_recall@5": 0.66,
+    "NanoMSMARCO_cosine_recall@1": 0.3,
+    "NanoMSMARCO_cosine_recall@3": 0.5,
+    "NanoMSMARCO_cosine_recall@5": 0.58,
     "NanoMSMARCO_cosine_recall@10": 0.7,
-    "NanoMSMARCO_cosine_ndcg@10": 0.5303422656736582,
-    "NanoMSMARCO_cosine_mrr@10": 0.4747460317460317,
-    "NanoMSMARCO_cosine_map@100": 0.48845125969077435,
+    "NanoMSMARCO_cosine_ndcg@10": 0.49319518919591504,
+    "NanoMSMARCO_cosine_mrr@10": 0.4282222222222222,
+    "NanoMSMARCO_cosine_map@100": 0.44089915437302396,
     "NanoNFCorpus_cosine_accuracy@1": 0.36,
     "NanoNFCorpus_cosine_accuracy@3": 0.48,
     "NanoNFCorpus_cosine_accuracy@5": 0.5,
-    "NanoNFCorpus_cosine_accuracy@10": 0.64,
+    "NanoNFCorpus_cosine_accuracy@10": 0.62,
     "NanoNFCorpus_cosine_precision@1": 0.36,
-    "NanoNFCorpus_cosine_precision@3": 0.3133333333333333,
-    "NanoNFCorpus_cosine_precision@5": 0.29200000000000004,
-    "NanoNFCorpus_cosine_precision@10": 0.26199999999999996,
-    "NanoNFCorpus_cosine_recall@1": 0.011117260803746984,
-    "NanoNFCorpus_cosine_recall@3": 0.052618880243359395,
-    "NanoNFCorpus_cosine_recall@5": 0.07334367009403865,
-    "NanoNFCorpus_cosine_recall@10": 0.11778483188857766,
-    "NanoNFCorpus_cosine_ndcg@10": 0.2943241147857984,
-    "NanoNFCorpus_cosine_mrr@10": 0.43522222222222234,
-    "NanoNFCorpus_cosine_map@100": 0.121057858108288,
-    "NanoNQ_cosine_accuracy@1": 0.44,
-    "NanoNQ_cosine_accuracy@3": 0.56,
-    "NanoNQ_cosine_accuracy@5": 0.64,
-    "NanoNQ_cosine_accuracy@10": 0.74,
-    "NanoNQ_cosine_precision@1": 0.44,
-    "NanoNQ_cosine_precision@3": 0.19333333333333333,
-    "NanoNQ_cosine_precision@5": 0.132,
-    "NanoNQ_cosine_precision@10": 0.078,
-    "NanoNQ_cosine_recall@1": 0.41,
-    "NanoNQ_cosine_recall@3": 0.53,
-    "NanoNQ_cosine_recall@5": 0.61,
-    "NanoNQ_cosine_recall@10": 0.7,
-    "NanoNQ_cosine_ndcg@10": 0.5519763173860046,
-    "NanoNQ_cosine_mrr@10": 0.523047619047619,
-    "NanoNQ_cosine_map@100": 0.5093692007660835,
+    "NanoNFCorpus_cosine_precision@3": 0.3,
+    "NanoNFCorpus_cosine_precision@5": 0.284,
+    "NanoNFCorpus_cosine_precision@10": 0.23399999999999999,
+    "NanoNFCorpus_cosine_recall@1": 0.012173359206591558,
+    "NanoNFCorpus_cosine_recall@3": 0.028722229702908417,
+    "NanoNFCorpus_cosine_recall@5": 0.04538392607412603,
+    "NanoNFCorpus_cosine_recall@10": 0.0669521595133137,
+    "NanoNFCorpus_cosine_ndcg@10": 0.2590743459873399,
+    "NanoNFCorpus_cosine_mrr@10": 0.43173809523809525,
+    "NanoNFCorpus_cosine_map@100": 0.08094835917197184,
+    "NanoNQ_cosine_accuracy@1": 0.26,
+    "NanoNQ_cosine_accuracy@3": 0.38,
+    "NanoNQ_cosine_accuracy@5": 0.48,
+    "NanoNQ_cosine_accuracy@10": 0.54,
+    "NanoNQ_cosine_precision@1": 0.26,
+    "NanoNQ_cosine_precision@3": 0.13333333333333333,
+    "NanoNQ_cosine_precision@5": 0.1,
+    "NanoNQ_cosine_precision@10": 0.05600000000000001,
+    "NanoNQ_cosine_recall@1": 0.23,
+    "NanoNQ_cosine_recall@3": 0.35,
+    "NanoNQ_cosine_recall@5": 0.45,
+    "NanoNQ_cosine_recall@10": 0.51,
+    "NanoNQ_cosine_ndcg@10": 0.3731343310366586,
+    "NanoNQ_cosine_mrr@10": 0.34907936507936504,
+    "NanoNQ_cosine_map@100": 0.33487673362538833,
     "NanoQuoraRetrieval_cosine_accuracy@1": 0.8,
-    "NanoQuoraRetrieval_cosine_accuracy@3": 0.94,
-    "NanoQuoraRetrieval_cosine_accuracy@5": 0.94,
+    "NanoQuoraRetrieval_cosine_accuracy@3": 0.9,
+    "NanoQuoraRetrieval_cosine_accuracy@5": 0.92,
     "NanoQuoraRetrieval_cosine_accuracy@10": 0.96,
     "NanoQuoraRetrieval_cosine_precision@1": 0.8,
-    "NanoQuoraRetrieval_cosine_precision@3": 0.4,
-    "NanoQuoraRetrieval_cosine_precision@5": 0.25199999999999995,
+    "NanoQuoraRetrieval_cosine_precision@3": 0.3733333333333333,
+    "NanoQuoraRetrieval_cosine_precision@5": 0.23199999999999996,
     "NanoQuoraRetrieval_cosine_precision@10": 0.12799999999999997,
-    "NanoQuoraRetrieval_cosine_recall@1": 0.6973333333333332,
-    "NanoQuoraRetrieval_cosine_recall@3": 0.9086666666666667,
-    "NanoQuoraRetrieval_cosine_recall@5": 0.9259999999999999,
+    "NanoQuoraRetrieval_cosine_recall@1": 0.7006666666666667,
+    "NanoQuoraRetrieval_cosine_recall@3": 0.862,
+    "NanoQuoraRetrieval_cosine_recall@5": 0.8886666666666667,
     "NanoQuoraRetrieval_cosine_recall@10": 0.946,
-    "NanoQuoraRetrieval_cosine_ndcg@10": 0.8793556978310312,
-    "NanoQuoraRetrieval_cosine_mrr@10": 0.8655555555555554,
-    "NanoQuoraRetrieval_cosine_map@100": 0.8572134707397865,
+    "NanoQuoraRetrieval_cosine_ndcg@10": 0.8709345901262452,
+    "NanoQuoraRetrieval_cosine_mrr@10": 0.8575,
+    "NanoQuoraRetrieval_cosine_map@100": 0.8417246177735308,
     "NanoSCIDOCS_cosine_accuracy@1": 0.44,
-    "NanoSCIDOCS_cosine_accuracy@3": 0.68,
-    "NanoSCIDOCS_cosine_accuracy@5": 0.72,
-    "NanoSCIDOCS_cosine_accuracy@10": 0.88,
+    "NanoSCIDOCS_cosine_accuracy@3": 0.62,
+    "NanoSCIDOCS_cosine_accuracy@5": 0.7,
+    "NanoSCIDOCS_cosine_accuracy@10": 0.8,
     "NanoSCIDOCS_cosine_precision@1": 0.44,
-    "NanoSCIDOCS_cosine_precision@3": 0.3533333333333333,
-    "NanoSCIDOCS_cosine_precision@5": 0.28,
-    "NanoSCIDOCS_cosine_precision@10": 0.19399999999999995,
-    "NanoSCIDOCS_cosine_recall@1": 0.09266666666666667,
-    "NanoSCIDOCS_cosine_recall@3": 0.21666666666666667,
-    "NanoSCIDOCS_cosine_recall@5": 0.2856666666666667,
-    "NanoSCIDOCS_cosine_recall@10": 0.39666666666666656,
-    "NanoSCIDOCS_cosine_ndcg@10": 0.3839901352188253,
-    "NanoSCIDOCS_cosine_mrr@10": 0.5817936507936508,
-    "NanoSCIDOCS_cosine_map@100": 0.29483854671038273,
-    "NanoArguAna_cosine_accuracy@1": 0.16,
-    "NanoArguAna_cosine_accuracy@3": 0.42,
-    "NanoArguAna_cosine_accuracy@5": 0.56,
-    "NanoArguAna_cosine_accuracy@10": 0.8,
-    "NanoArguAna_cosine_precision@1": 0.16,
-    "NanoArguAna_cosine_precision@3": 0.13999999999999999,
-    "NanoArguAna_cosine_precision@5": 0.11200000000000003,
-    "NanoArguAna_cosine_precision@10": 0.08,
-    "NanoArguAna_cosine_recall@1": 0.16,
-    "NanoArguAna_cosine_recall@3": 0.42,
-    "NanoArguAna_cosine_recall@5": 0.56,
-    "NanoArguAna_cosine_recall@10": 0.8,
-    "NanoArguAna_cosine_ndcg@10": 0.4541392479306418,
-    "NanoArguAna_cosine_mrr@10": 0.346095238095238,
-    "NanoArguAna_cosine_map@100": 0.3511114131364851,
-    "NanoSciFact_cosine_accuracy@1": 0.46,
-    "NanoSciFact_cosine_accuracy@3": 0.54,
-    "NanoSciFact_cosine_accuracy@5": 0.64,
-    "NanoSciFact_cosine_accuracy@10": 0.74,
-    "NanoSciFact_cosine_precision@1": 0.46,
-    "NanoSciFact_cosine_precision@3": 0.2,
-    "NanoSciFact_cosine_precision@5": 0.14400000000000002,
-    "NanoSciFact_cosine_precision@10": 0.08599999999999998,
-    "NanoSciFact_cosine_recall@1": 0.415,
-    "NanoSciFact_cosine_recall@3": 0.52,
-    "NanoSciFact_cosine_recall@5": 0.625,
-    "NanoSciFact_cosine_recall@10": 0.74,
-    "NanoSciFact_cosine_ndcg@10": 0.5798929270624772,
-    "NanoSciFact_cosine_mrr@10": 0.5398333333333334,
-    "NanoSciFact_cosine_map@100": 0.5303142135642136,
-    "NanoTouche2020_cosine_accuracy@1": 0.6530612244897959,
-    "NanoTouche2020_cosine_accuracy@3": 0.7755102040816326,
-    "NanoTouche2020_cosine_accuracy@5": 0.8571428571428571,
-    "NanoTouche2020_cosine_accuracy@10": 0.9387755102040817,
-    "NanoTouche2020_cosine_precision@1": 0.6530612244897959,
-    "NanoTouche2020_cosine_precision@3": 0.5374149659863945,
-    "NanoTouche2020_cosine_precision@5": 0.5020408163265306,
-    "NanoTouche2020_cosine_precision@10": 0.4040816326530612,
-    "NanoTouche2020_cosine_recall@1": 0.04497799044877029,
-    "NanoTouche2020_cosine_recall@3": 0.11546047315036259,
-    "NanoTouche2020_cosine_recall@5": 0.18376483178712996,
-    "NanoTouche2020_cosine_recall@10": 0.2772240574916768,
-    "NanoTouche2020_cosine_ndcg@10": 0.4711126371779877,
-    "NanoTouche2020_cosine_mrr@10": 0.7406705539358601,
-    "NanoTouche2020_cosine_map@100": 0.35552822693119057,
-    "NanoBEIR_mean_cosine_accuracy@1": 0.4794662480376766,
-    "NanoBEIR_mean_cosine_accuracy@3": 0.6550392464678179,
-    "NanoBEIR_mean_cosine_accuracy@5": 0.7167032967032967,
-    "NanoBEIR_mean_cosine_accuracy@10": 0.8060596546310832,
-    "NanoBEIR_mean_cosine_precision@1": 0.4794662480376766,
-    "NanoBEIR_mean_cosine_precision@3": 0.29723704866562006,
-    "NanoBEIR_mean_cosine_precision@5": 0.22723390894819467,
-    "NanoBEIR_mean_cosine_precision@10": 0.1584678178963893,
-    "NanoBEIR_mean_cosine_recall@1": 0.26612830766551065,
-    "NanoBEIR_mean_cosine_recall@3": 0.41246090821921455,
-    "NanoBEIR_mean_cosine_recall@5": 0.4764429392718,
-    "NanoBEIR_mean_cosine_recall@10": 0.5559730399550165,
-    "NanoBEIR_mean_cosine_ndcg@10": 0.5087337546066613,
-    "NanoBEIR_mean_cosine_mrr@10": 0.5851309461513544,
-    "NanoBEIR_mean_cosine_map@100": 0.42587177797164666
+    "NanoSCIDOCS_cosine_precision@3": 0.2866666666666667,
+    "NanoSCIDOCS_cosine_precision@5": 0.21999999999999997,
+    "NanoSCIDOCS_cosine_precision@10": 0.16400000000000003,
+    "NanoSCIDOCS_cosine_recall@1": 0.09,
+    "NanoSCIDOCS_cosine_recall@3": 0.175,
+    "NanoSCIDOCS_cosine_recall@5": 0.22399999999999998,
+    "NanoSCIDOCS_cosine_recall@10": 0.3356666666666667,
+    "NanoSCIDOCS_cosine_ndcg@10": 0.32838811799960327,
+    "NanoSCIDOCS_cosine_mrr@10": 0.5561031746031745,
+    "NanoSCIDOCS_cosine_map@100": 0.24434998843859707,
+    "NanoArguAna_cosine_accuracy@1": 0.2,
+    "NanoArguAna_cosine_accuracy@3": 0.36,
+    "NanoArguAna_cosine_accuracy@5": 0.48,
+    "NanoArguAna_cosine_accuracy@10": 0.64,
+    "NanoArguAna_cosine_precision@1": 0.2,
+    "NanoArguAna_cosine_precision@3": 0.11999999999999998,
+    "NanoArguAna_cosine_precision@5": 0.09600000000000002,
+    "NanoArguAna_cosine_precision@10": 0.06400000000000002,
+    "NanoArguAna_cosine_recall@1": 0.2,
+    "NanoArguAna_cosine_recall@3": 0.36,
+    "NanoArguAna_cosine_recall@5": 0.48,
+    "NanoArguAna_cosine_recall@10": 0.64,
+    "NanoArguAna_cosine_ndcg@10": 0.399971817141543,
+    "NanoArguAna_cosine_mrr@10": 0.3259920634920635,
+    "NanoArguAna_cosine_map@100": 0.33708074446236025,
+    "NanoSciFact_cosine_accuracy@1": 0.3,
+    "NanoSciFact_cosine_accuracy@3": 0.5,
+    "NanoSciFact_cosine_accuracy@5": 0.52,
+    "NanoSciFact_cosine_accuracy@10": 0.62,
+    "NanoSciFact_cosine_precision@1": 0.3,
+    "NanoSciFact_cosine_precision@3": 0.1733333333333333,
+    "NanoSciFact_cosine_precision@5": 0.11600000000000002,
+    "NanoSciFact_cosine_precision@10": 0.07,
+    "NanoSciFact_cosine_recall@1": 0.265,
+    "NanoSciFact_cosine_recall@3": 0.46,
+    "NanoSciFact_cosine_recall@5": 0.495,
+    "NanoSciFact_cosine_recall@10": 0.6,
+    "NanoSciFact_cosine_ndcg@10": 0.43558334687061145,
+    "NanoSciFact_cosine_mrr@10": 0.4002698412698413,
+    "NanoSciFact_cosine_map@100": 0.3861669168464833,
+    "NanoTouche2020_cosine_accuracy@1": 0.6326530612244898,
+    "NanoTouche2020_cosine_accuracy@3": 0.8163265306122449,
+    "NanoTouche2020_cosine_accuracy@5": 0.8979591836734694,
+    "NanoTouche2020_cosine_accuracy@10": 0.9591836734693877,
+    "NanoTouche2020_cosine_precision@1": 0.6326530612244898,
+    "NanoTouche2020_cosine_precision@3": 0.4965986394557823,
+    "NanoTouche2020_cosine_precision@5": 0.46938775510204084,
+    "NanoTouche2020_cosine_precision@10": 0.37142857142857144,
+    "NanoTouche2020_cosine_recall@1": 0.04499413135420742,
+    "NanoTouche2020_cosine_recall@3": 0.1065943935391371,
+    "NanoTouche2020_cosine_recall@5": 0.16649967473172042,
+    "NanoTouche2020_cosine_recall@10": 0.24826882087723884,
+    "NanoTouche2020_cosine_ndcg@10": 0.43458124412524113,
+    "NanoTouche2020_cosine_mrr@10": 0.7421768707482992,
+    "NanoTouche2020_cosine_map@100": 0.31599660374216376,
+    "NanoBEIR_mean_cosine_accuracy@1": 0.40097331240188383,
+    "NanoBEIR_mean_cosine_accuracy@3": 0.5658712715855574,
+    "NanoBEIR_mean_cosine_accuracy@5": 0.6352276295133438,
+    "NanoBEIR_mean_cosine_accuracy@10": 0.7276295133437991,
+    "NanoBEIR_mean_cosine_precision@1": 0.40097331240188383,
+    "NanoBEIR_mean_cosine_precision@3": 0.24948194662480377,
+    "NanoBEIR_mean_cosine_precision@5": 0.19610675039246467,
+    "NanoBEIR_mean_cosine_precision@10": 0.1381098901098901,
+    "NanoBEIR_mean_cosine_recall@1": 0.21512604500566113,
+    "NanoBEIR_mean_cosine_recall@3": 0.33411180979148064,
+    "NanoBEIR_mean_cosine_recall@5": 0.39161958804398667,
+    "NanoBEIR_mean_cosine_recall@10": 0.4734199547405025,
+    "NanoBEIR_mean_cosine_ndcg@10": 0.4271640152331507,
+    "NanoBEIR_mean_cosine_mrr@10": 0.5034684283969997,
+    "NanoBEIR_mean_cosine_map@100": 0.3491355302958642
   },
   "beir_touche2020": {
-    "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.7755102040816326,
-    "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.9795918367346939,
-    "BeIR-touche2020-subset-test_cosine_accuracy@5": 1.0,
+    "BeIR-touche2020-subset-test_cosine_accuracy@1": 0.7551020408163265,
+    "BeIR-touche2020-subset-test_cosine_accuracy@3": 0.9387755102040817,
+    "BeIR-touche2020-subset-test_cosine_accuracy@5": 0.9591836734693877,
     "BeIR-touche2020-subset-test_cosine_accuracy@10": 1.0,
-    "BeIR-touche2020-subset-test_cosine_precision@1": 0.7755102040816326,
-    "BeIR-touche2020-subset-test_cosine_precision@3": 0.7482993197278911,
-    "BeIR-touche2020-subset-test_cosine_precision@5": 0.7142857142857143,
-    "BeIR-touche2020-subset-test_cosine_precision@10": 0.6122448979591837,
-    "BeIR-touche2020-subset-test_cosine_recall@1": 0.01706832759711131,
-    "BeIR-touche2020-subset-test_cosine_recall@3": 0.049401730544661945,
-    "BeIR-touche2020-subset-test_cosine_recall@5": 0.07867619617707583,
-    "BeIR-touche2020-subset-test_cosine_recall@10": 0.1349240729674531,
-    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.653970278908209,
-    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.8714285714285713,
-    "BeIR-touche2020-subset-test_cosine_map@100": 0.2786997022824942
+    "BeIR-touche2020-subset-test_cosine_precision@1": 0.7551020408163265,
+    "BeIR-touche2020-subset-test_cosine_precision@3": 0.7210884353741496,
+    "BeIR-touche2020-subset-test_cosine_precision@5": 0.6612244897959183,
+    "BeIR-touche2020-subset-test_cosine_precision@10": 0.5591836734693877,
+    "BeIR-touche2020-subset-test_cosine_recall@1": 0.01662880113717669,
+    "BeIR-touche2020-subset-test_cosine_recall@3": 0.04763575042744458,
+    "BeIR-touche2020-subset-test_cosine_recall@5": 0.07282683231615908,
+    "BeIR-touche2020-subset-test_cosine_recall@10": 0.12302205261034137,
+    "BeIR-touche2020-subset-test_cosine_ndcg@10": 0.6039860530659029,
+    "BeIR-touche2020-subset-test_cosine_mrr@10": 0.8510689990281828,
+    "BeIR-touche2020-subset-test_cosine_map@100": 0.24094937083231965
   }
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:2a98f1622a4a42534215d1502cad7fd6c4bcf256ac3afec2bc8bdf6396352a14
-size 90864192
+oid sha256:ae95ff24f896d304a3d1a404f7e677934f07f6d74928172271b9f09a2e86b812
+size 133462128

tokenizer_config.json

@@ -48,7 +48,7 @@
   "extra_special_tokens": {},
   "mask_token": "[MASK]",
   "max_length": 128,
-  "model_max_length": 256,
+  "model_max_length": 128,
   "never_split": null,
   "pad_to_multiple_of": null,
   "pad_token": "[PAD]",

training_args.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d4c7ac1d7a032af33aae76aedacd113fc0586e4cb0d439c6847ffbd738908289
+oid sha256:83964be082839d4eb3eac00180ad488596471dcf1563bd0f3ea8ba9c67675aa7
 size 6161