Step 0 -- Accuracy: 0.275 -- macro_f1: 0.24245894645844043 -- loss: 1.1975505352020264

Step 100 -- Accuracy: 0.8230113636363636 -- macro_f1: 0.8247917227891541 -- loss: 0.5072745084762573

Step 200 -- Accuracy: 0.8585227272727273 -- macro_f1: 0.8596474113005192 -- loss: 0.3576969504356384

Step 300 -- Accuracy: 0.8616477272727273 -- macro_f1: 0.8619445917534628 -- loss: 0.22678352892398834

Step 400 -- Accuracy: 0.8710227272727272 -- macro_f1: 0.8713149438253084 -- loss: 0.3302939534187317

Step 500 -- Accuracy: 0.8491477272727272 -- macro_f1: 0.8497535984618637 -- loss: 0.8534196615219116

Step 600 -- Accuracy: 0.8627840909090909 -- macro_f1: 0.8630171351987245 -- loss: 0.27207863330841064

Step 700 -- Accuracy: 0.8676136363636363 -- macro_f1: 0.8681189318753203 -- loss: 0.5472040772438049

Step 800 -- Accuracy: 0.8480113636363636 -- macro_f1: 0.8474828960740969 -- loss: 0.20389704406261444

Step 900 -- Accuracy: 0.8625 -- macro_f1: 0.8627369387200629 -- loss: 0.7003616094589233

Step 1000 -- Accuracy: 0.8471590909090909 -- macro_f1: 0.8474576933366409 -- loss: 0.39897170662879944

Step 1100 -- Accuracy: 0.8647727272727272 -- macro_f1: 0.8648449015557045 -- loss: 0.30028393864631653

Step 1200 -- Accuracy: 0.8355113636363637 -- macro_f1: 0.8357176579844655 -- loss: 0.5329824090003967

Step 1300 -- Accuracy: 0.8318181818181818 -- macro_f1: 0.832158484567787 -- loss: 0.04946904629468918

Step 1400 -- Accuracy: 0.8275568181818181 -- macro_f1: 0.8270568913757921 -- loss: 0.290753036737442

Step 1500 -- Accuracy: 0.8619318181818182 -- macro_f1: 0.8620216901652552 -- loss: 0.17760200798511505

Step 1600 -- Accuracy: 0.8366477272727273 -- macro_f1: 0.8372501215741125 -- loss: 0.18745465576648712

Step 1700 -- Accuracy: 0.8556818181818182 -- macro_f1: 0.8555692365839257 -- loss: 0.09077112376689911

Step 1800 -- Accuracy: 0.8571022727272727 -- macro_f1: 0.8569408344903815 -- loss: 0.24079212546348572

Step 1900 -- Accuracy: 0.8122159090909091 -- macro_f1: 0.8117034674801616 -- loss: 0.3681311309337616

Step 2000 -- Accuracy: 0.8318181818181818 -- macro_f1: 0.8319676688379705 -- loss: 0.2374744713306427

Step 2100 -- Accuracy: 0.8443181818181819 -- macro_f1: 0.8442918629955193 -- loss: 0.4600515365600586

Step 2200 -- Accuracy: 0.8278409090909091 -- macro_f1: 0.8269904995679983 -- loss: 0.3283902704715729

Step 2300 -- Accuracy: 0.8298295454545455 -- macro_f1: 0.8299882032010862 -- loss: 1.0965081453323364

Step 2400 -- Accuracy: 0.8159090909090909 -- macro_f1: 0.8159808860940237 -- loss: 0.7295159697532654

Step 2500 -- Accuracy: 0.8159090909090909 -- macro_f1: 0.8142475187664063 -- loss: 0.3925968408584595

Step 2600 -- Accuracy: 0.8204545454545454 -- macro_f1: 0.820545798600696 -- loss: 0.3808274567127228

Step 2700 -- Accuracy: 0.8198863636363637 -- macro_f1: 0.8199413434559383 -- loss: 0.26008090376853943

Step 2800 -- Accuracy: 0.8056818181818182 -- macro_f1: 0.8051566431375038 -- loss: 0.20567485690116882

Step 2900 -- Accuracy: 0.784375 -- macro_f1: 0.7848921849530183 -- loss: 0.5506788492202759

Step 3000 -- Accuracy: 0.8153409090909091 -- macro_f1: 0.8150634367874668 -- loss: 0.4250873923301697

Step 3100 -- Accuracy: 0.7991477272727273 -- macro_f1: 0.8000715520252392 -- loss: 0.4798588752746582

Step 3200 -- Accuracy: 0.7840909090909091 -- macro_f1: 0.7836356305606565 -- loss: 0.5604580640792847

Step 3300 -- Accuracy: 0.7977272727272727 -- macro_f1: 0.7965403402362528 -- loss: 0.26682722568511963

Step 3400 -- Accuracy: 0.809375 -- macro_f1: 0.8087947373143304 -- loss: 0.3252097964286804

Step 3500 -- Accuracy: 0.7568181818181818 -- macro_f1: 0.7548780108676749 -- loss: 0.9467527866363525

Step 3600 -- Accuracy: 0.7889204545454546 -- macro_f1: 0.7892382882596812 -- loss: 0.29441171884536743

Step 3700 -- Accuracy: 0.7227272727272728 -- macro_f1: 0.7227876418017654 -- loss: 0.8389160633087158