Step 0 -- Accuracy: 0.3039772727272727 -- macro_f1: 0.20810584530698015 -- loss: 1.0453389883041382

Step 100 -- Accuracy: 0.859375 -- macro_f1: 0.8598470398571504 -- loss: 0.11795929819345474

Step 200 -- Accuracy: 0.8747159090909091 -- macro_f1: 0.8755251824421424 -- loss: 0.22730453312397003

Step 300 -- Accuracy: 0.8536931818181818 -- macro_f1: 0.8533303214529117 -- loss: 0.18725647032260895

Step 400 -- Accuracy: 0.8690340909090909 -- macro_f1: 0.8687299763460793 -- loss: 0.28860458731651306

Step 500 -- Accuracy: 0.8798295454545455 -- macro_f1: 0.8802316356122608 -- loss: 0.6372634172439575

Step 600 -- Accuracy: 0.8610795454545455 -- macro_f1: 0.8612099869711884 -- loss: 0.41530805826187134

Step 700 -- Accuracy: 0.8491477272727272 -- macro_f1: 0.849751664990205 -- loss: 0.5970628261566162

Step 800 -- Accuracy: 0.8764204545454546 -- macro_f1: 0.8766266441048876 -- loss: 0.2515469491481781

Step 900 -- Accuracy: 0.8710227272727272 -- macro_f1: 0.8712350728851791 -- loss: 0.619756817817688

Step 1000 -- Accuracy: 0.8744318181818181 -- macro_f1: 0.8746062203201398 -- loss: 0.5634986758232117

Step 1100 -- Accuracy: 0.8735795454545454 -- macro_f1: 0.8735921715063891 -- loss: 0.2514641284942627

Step 1200 -- Accuracy: 0.8375 -- macro_f1: 0.8368621880475362 -- loss: 0.44521981477737427

Step 1300 -- Accuracy: 0.8551136363636364 -- macro_f1: 0.8555806721970362 -- loss: 0.048632219433784485

Step 1400 -- Accuracy: 0.8508522727272727 -- macro_f1: 0.8506097642423027 -- loss: 0.24613773822784424

Step 1500 -- Accuracy: 0.8673295454545454 -- macro_f1: 0.8671847303392856 -- loss: 0.1494443565607071

Step 1600 -- Accuracy: 0.834375 -- macro_f1: 0.8342641066244109 -- loss: 0.17161081731319427

Step 1700 -- Accuracy: 0.865625 -- macro_f1: 0.8651594643017528 -- loss: 0.154042050242424

Step 1800 -- Accuracy: 0.865909090909091 -- macro_f1: 0.8657615265484808 -- loss: 0.1435176134109497

Step 1900 -- Accuracy: 0.8176136363636364 -- macro_f1: 0.8171586288909666 -- loss: 0.09292535483837128

Step 2000 -- Accuracy: 0.8440340909090909 -- macro_f1: 0.843042759250924 -- loss: 0.34320467710494995

Step 2100 -- Accuracy: 0.8428977272727273 -- macro_f1: 0.8428498174495328 -- loss: 0.5764151811599731

Step 2200 -- Accuracy: 0.8417613636363637 -- macro_f1: 0.8418818479059557 -- loss: 0.28757143020629883

Step 2300 -- Accuracy: 0.840625 -- macro_f1: 0.8406394626850148 -- loss: 0.8960273861885071

Step 2400 -- Accuracy: 0.8142045454545455 -- macro_f1: 0.8140964442024906 -- loss: 0.8550783395767212

Step 2500 -- Accuracy: 0.8144886363636363 -- macro_f1: 0.8147455224461172 -- loss: 0.39625313878059387

Step 2600 -- Accuracy: 0.8053977272727273 -- macro_f1: 0.8021211300036969 -- loss: 0.3774358034133911

Step 2700 -- Accuracy: 0.8292613636363636 -- macro_f1: 0.8292382309283113 -- loss: 0.16644884645938873

Step 2800 -- Accuracy: 0.8150568181818182 -- macro_f1: 0.814290740222007 -- loss: 0.237399160861969

Step 2900 -- Accuracy: 0.8107954545454545 -- macro_f1: 0.8111709474507229 -- loss: 0.5621077418327332

Step 3000 -- Accuracy: 0.7926136363636364 -- macro_f1: 0.7930916669737708 -- loss: 0.4253169298171997

Step 3100 -- Accuracy: 0.8099431818181818 -- macro_f1: 0.8102288703246834 -- loss: 0.43165838718414307

Step 3200 -- Accuracy: 0.772159090909091 -- macro_f1: 0.7717788019596861 -- loss: 0.673878014087677

Step 3300 -- Accuracy: 0.7897727272727273 -- macro_f1: 0.7895567869064662 -- loss: 0.1990412026643753

Step 3400 -- Accuracy: 0.8008522727272728 -- macro_f1: 0.7997998535844976 -- loss: 0.4523601531982422

Step 3500 -- Accuracy: 0.7798295454545454 -- macro_f1: 0.7780260696858295 -- loss: 0.8848648071289062

Step 3600 -- Accuracy: 0.7775568181818182 -- macro_f1: 0.7779453966289696 -- loss: 0.5041539669036865

Step 3700 -- Accuracy: 0.709659090909091 -- macro_f1: 0.7069128111001839 -- loss: 0.6758942604064941