Global epoch: 0, step: 10000, cor_acc = 0.5760617477472523 Global epoch: 0, step: 10000, cor_f1 = 0.517420477137177 Global epoch: 0, step: 10000, cor_precision = 0.5578747119661326 Global epoch: 0, step: 10000, cor_recall = 0.4824366282033458 Global epoch: 0, step: 10000, det_acc = 0.7364353876192833 Global epoch: 0, step: 10000, det_f1 = 0.7348036779324055 Global epoch: 0, step: 10000, det_precision = 0.7922538985049032 Global epoch: 0, step: 10000, det_recall = 0.6851221094582696 Global epoch: 0, step: 10000, eval_cor_loss = 0.02755504156968236 Global epoch: 0, step: 10000, eval_cor_macbert_loss = 0.03497673619573494 Global epoch: 0, step: 10000, eval_det_loss = 0.09709695273831735 Global epoch: 0, step: 10000, eval_det_macbert_loss = 0.09540795864238658 Global epoch: 0, step: 10000, eval_loss = 0.041013875188771774 Global epoch: 0, step: 10000, global_step = 10000 Global epoch: 0, step: 10000, lr = 2.9994054140933278e-05 Global epoch: 0, step: 10000, train_cor_loss = 0.16637890402522754 Global epoch: 0, step: 10000, train_cor_macbert_loss = 0.15020995716522448 Global epoch: 0, step: 10000, train_det_loss = 0.10245838651936501 Global epoch: 0, step: 10000, train_det_macbert_loss = 0.10107964973468334 Global epoch: 0, step: 10000, train_loss = 0.037453905746468806 Global epoch: 0, step: 20000, cor_acc = 0.606477280019067 Global epoch: 0, step: 20000, cor_f1 = 0.5543701649662889 Global epoch: 0, step: 20000, cor_precision = 0.5891741755447468 Global epoch: 0, step: 20000, cor_recall = 0.5234487232957968 Global epoch: 0, step: 20000, det_acc = 0.753944027353812 Global epoch: 0, step: 20000, det_f1 = 0.7517530352202106 Global epoch: 0, step: 20000, det_precision = 0.7989489744024411 Global epoch: 0, step: 20000, det_recall = 0.7098220492145141 Global epoch: 0, step: 20000, eval_cor_loss = 0.021600455334980714 Global epoch: 0, step: 20000, eval_cor_macbert_loss = 0.03197105644924424 Global epoch: 0, step: 20000, eval_det_loss = 0.09696177433388774 Global epoch: 0, step: 20000, eval_det_macbert_loss = 0.09534921718155732 Global epoch: 0, step: 20000, eval_loss = 0.03719121807811023 Global epoch: 0, step: 20000, global_step = 20000 Global epoch: 0, step: 20000, lr = 2.9975912046845362e-05 Global epoch: 0, step: 20000, train_cor_loss = 0.40033843709974837 Global epoch: 0, step: 20000, train_cor_macbert_loss = 0.42073205082296383 Global epoch: 0, step: 20000, train_det_loss = 0.4047715658448325 Global epoch: 0, step: 20000, train_det_macbert_loss = 0.39783582574399273 Global epoch: 0, step: 20000, train_loss = 0.10228763100169097 Global epoch: 0, step: 30000, cor_acc = 0.6288168376279918 Global epoch: 0, step: 30000, cor_f1 = 0.5817470026914607 Global epoch: 0, step: 30000, cor_precision = 0.6162459177854959 Global epoch: 0, step: 30000, cor_recall = 0.5509059734000649 Global epoch: 0, step: 30000, det_acc = 0.7669884222973902 Global epoch: 0, step: 30000, det_f1 = 0.7661487643748471 Global epoch: 0, step: 30000, det_precision = 0.8115831216629517 Global epoch: 0, step: 30000, det_recall = 0.7255317669956902 Global epoch: 0, step: 30000, eval_cor_loss = 0.018870065465758708 Global epoch: 0, step: 30000, eval_cor_macbert_loss = 0.030062583396366898 Global epoch: 0, step: 30000, eval_det_loss = 0.09688241297733535 Global epoch: 0, step: 30000, eval_det_macbert_loss = 0.09530232426699778 Global epoch: 0, step: 30000, eval_loss = 0.03521023219332811 Global epoch: 0, step: 30000, global_step = 30000 Global epoch: 0, step: 30000, lr = 2.9945587476150035e-05 Global epoch: 0, step: 30000, train_cor_loss = 0.07440343986249619 Global epoch: 0, step: 30000, train_cor_macbert_loss = 0.08072522892201535 Global epoch: 0, step: 30000, train_det_loss = 0.08119228218164676 Global epoch: 0, step: 30000, train_det_macbert_loss = 0.07982934504728463 Global epoch: 0, step: 30000, train_loss = 0.019501577161004903 Global epoch: 0, step: 40000, cor_acc = 0.6511930625452612 Global epoch: 0, step: 40000, cor_f1 = 0.6105510195305061 Global epoch: 0, step: 40000, cor_precision = 0.6499247923615199 Global epoch: 0, step: 40000, cor_recall = 0.5756754251818899 Global epoch: 0, step: 40000, det_acc = 0.7738635426119957 Global epoch: 0, step: 40000, det_f1 = 0.7749783438081721 Global epoch: 0, step: 40000, det_precision = 0.8249558563861095 Global epoch: 0, step: 40000, det_recall = 0.7307104129014319 Global epoch: 0, step: 40000, eval_cor_loss = 0.017164383152932828 Global epoch: 0, step: 40000, eval_cor_macbert_loss = 0.028549492777997152 Global epoch: 0, step: 40000, eval_det_loss = 0.0968078388929437 Global epoch: 0, step: 40000, eval_det_macbert_loss = 0.09526594171021488 Global epoch: 0, step: 40000, eval_loss = 0.03383393191473902 Global epoch: 0, step: 40000, global_step = 40000 Global epoch: 0, step: 40000, lr = 2.9903105097019234e-05 Global epoch: 0, step: 40000, train_cor_loss = 0.1760299022952686 Global epoch: 0, step: 40000, train_cor_macbert_loss = 0.1942309295242444 Global epoch: 0, step: 40000, train_det_loss = 0.20191652712516853 Global epoch: 0, step: 40000, train_det_macbert_loss = 0.19858354432727657 Global epoch: 0, step: 40000, train_loss = 0.04684959115699049 Global epoch: 0, step: 50000, cor_acc = 0.6625874286133341 Global epoch: 0, step: 50000, cor_f1 = 0.6227133868042793 Global epoch: 0, step: 50000, cor_precision = 0.6558646327393924 Global epoch: 0, step: 50000, cor_recall = 0.592752212799481 Global epoch: 0, step: 50000, det_acc = 0.7819945182374025 Global epoch: 0, step: 50000, det_f1 = 0.7812519017075813 Global epoch: 0, step: 50000, det_precision = 0.822843225227535 Global epoch: 0, step: 50000, det_recall = 0.7436628203345845 Global epoch: 0, step: 50000, eval_cor_loss = 0.01587513945144892 Global epoch: 0, step: 50000, eval_cor_macbert_loss = 0.02752522239420586 Global epoch: 0, step: 50000, eval_det_loss = 0.09676935055001815 Global epoch: 0, step: 50000, eval_det_macbert_loss = 0.09525397708254522 Global epoch: 0, step: 50000, eval_loss = 0.032846904459415696 Global epoch: 0, step: 50000, global_step = 50000 Global epoch: 0, step: 50000, lr = 2.98484994676547e-05 Global epoch: 0, step: 50000, train_cor_loss = 0.05696381209996449 Global epoch: 0, step: 50000, train_cor_macbert_loss = 0.0635468460281505 Global epoch: 0, step: 50000, train_det_loss = 0.06750950393676693 Global epoch: 0, step: 50000, train_det_macbert_loss = 0.06641238904553633 Global epoch: 0, step: 50000, train_loss = 0.015315293383025841 Global epoch: 0, step: 60000, cor_acc = 0.6716167532931826 Global epoch: 0, step: 60000, cor_f1 = 0.6332062223836329 Global epoch: 0, step: 60000, cor_precision = 0.6629908484802393 Global epoch: 0, step: 60000, cor_recall = 0.6059826683349553 Global epoch: 0, step: 60000, det_acc = 0.7893188130792289 Global epoch: 0, step: 60000, det_f1 = 0.7886447551600992 Global epoch: 0, step: 60000, det_precision = 0.825740867493092 Global epoch: 0, step: 60000, det_recall = 0.7547384030770656 Global epoch: 0, step: 60000, eval_cor_loss = 0.015069915684924617 Global epoch: 0, step: 60000, eval_cor_macbert_loss = 0.027036836567684044 Global epoch: 0, step: 60000, eval_det_loss = 0.09670754334892356 Global epoch: 0, step: 60000, eval_det_macbert_loss = 0.09523926801571081 Global epoch: 0, step: 60000, eval_loss = 0.032291381625058325 Global epoch: 0, step: 60000, global_step = 60000 Global epoch: 0, step: 60000, lr = 2.978181500817592e-05 Global epoch: 0, step: 60000, train_cor_loss = 0.11038520596981997 Global epoch: 0, step: 60000, train_cor_macbert_loss = 0.12415528979114172 Global epoch: 0, step: 60000, train_det_loss = 0.13449211598008604 Global epoch: 0, step: 60000, train_det_macbert_loss = 0.13235185763300733 Global epoch: 0, step: 60000, train_loss = 0.02992325309928183 Global epoch: 0, step: 70000, cor_acc = 0.6826902804132405 Global epoch: 0, step: 70000, cor_f1 = 0.6475158479085609 Global epoch: 0, step: 70000, cor_precision = 0.6788918541110688 Global epoch: 0, step: 70000, cor_recall = 0.6189119050929144 Global epoch: 0, step: 70000, det_acc = 0.7937280569076626 Global epoch: 0, step: 70000, det_f1 = 0.7943347514635831 Global epoch: 0, step: 70000, det_precision = 0.8328250095310713 Global epoch: 0, step: 70000, det_recall = 0.7592450994021965 Global epoch: 0, step: 70000, eval_cor_loss = 0.014224558398737106 Global epoch: 0, step: 70000, eval_cor_macbert_loss = 0.026147653754200972 Global epoch: 0, step: 70000, eval_det_loss = 0.09664877431373797 Global epoch: 0, step: 70000, eval_det_macbert_loss = 0.09521696318571116 Global epoch: 0, step: 70000, eval_loss = 0.03154812149301595 Global epoch: 0, step: 70000, global_step = 70000 Global epoch: 0, step: 70000, lr = 2.9703105964485586e-05 Global epoch: 0, step: 70000, train_cor_loss = 14.507786997708381 Global epoch: 0, step: 70000, train_cor_macbert_loss = 16.43217406734691 Global epoch: 0, step: 70000, train_det_loss = 18.103522603275014 Global epoch: 0, step: 70000, train_det_macbert_loss = 17.820088707563468 Global epoch: 0, step: 70000, train_loss = 3.9609386970212666 Global epoch: 0, step: 80000, cor_acc = 0.6883645463795617 Global epoch: 0, step: 80000, cor_f1 = 0.6540192380005095 Global epoch: 0, step: 80000, cor_precision = 0.6862765063768043 Global epoch: 0, step: 80000, cor_recall = 0.6246582325408963 Global epoch: 0, step: 80000, det_acc = 0.7955247550165461 Global epoch: 0, step: 80000, det_f1 = 0.7958176150216518 Global epoch: 0, step: 80000, det_precision = 0.8350686047399638 Global epoch: 0, step: 80000, det_recall = 0.7600908290467584 Global epoch: 0, step: 80000, eval_cor_loss = 0.013840348574079517 Global epoch: 0, step: 80000, eval_cor_macbert_loss = 0.025862808581479865 Global epoch: 0, step: 80000, eval_det_loss = 0.0966465382571096 Global epoch: 0, step: 80000, eval_det_macbert_loss = 0.09520950634496647 Global epoch: 0, step: 80000, eval_loss = 0.03126304619542859 Global epoch: 0, step: 80000, global_step = 80000 Global epoch: 0, step: 80000, lr = 2.9612436364142123e-05 Global epoch: 0, step: 80000, train_cor_loss = 0.07983245638290787 Global epoch: 0, step: 80000, train_cor_macbert_loss = 0.09087601449187581 Global epoch: 0, step: 80000, train_det_loss = 0.10116119374600506 Global epoch: 0, step: 80000, train_det_macbert_loss = 0.0995912614296069 Global epoch: 0, step: 80000, train_loss = 0.021901884230096022 Global epoch: 0, step: 90000, cor_acc = 0.6973113696156349 Global epoch: 0, step: 90000, cor_f1 = 0.6661733127904015 Global epoch: 0, step: 90000, cor_precision = 0.6991418604058974 Global epoch: 0, step: 90000, cor_recall = 0.6361740581120534 Global epoch: 0, step: 90000, det_acc = 0.7984398060299388 Global epoch: 0, step: 90000, det_f1 = 0.8000097053221561 Global epoch: 0, step: 90000, det_precision = 0.8396017417432711 Global epoch: 0, step: 90000, det_recall = 0.7639835024792623 Global epoch: 0, step: 90000, eval_cor_loss = 0.013236278385574169 Global epoch: 0, step: 90000, eval_cor_macbert_loss = 0.02525943082002898 Global epoch: 0, step: 90000, eval_det_loss = 0.0965870682535651 Global epoch: 0, step: 90000, eval_det_macbert_loss = 0.09517930360028766 Global epoch: 0, step: 90000, eval_loss = 0.030743155336295253 Global epoch: 0, step: 90000, global_step = 90000 Global epoch: 0, step: 90000, lr = 2.9509879964275093e-05 Global epoch: 0, step: 90000, train_cor_loss = 0.3045018796420776 Global epoch: 0, step: 90000, train_cor_macbert_loss = 0.348646783131653 Global epoch: 0, step: 90000, train_det_loss = 0.39407741724400147 Global epoch: 0, step: 90000, train_det_macbert_loss = 0.38803321373372646 Global epoch: 0, step: 90000, train_loss = 0.08406162230291783 Global epoch: 0, step: 100000, cor_acc = 0.7016931129628102 Global epoch: 0, step: 100000, cor_f1 = 0.6702761561961224 Global epoch: 0, step: 100000, cor_precision = 0.7013634809910241 Global epoch: 0, step: 100000, cor_recall = 0.6418277028592613 Global epoch: 0, step: 100000, det_acc = 0.8023998753311516 Global epoch: 0, step: 100000, det_f1 = 0.8031940957623785 Global epoch: 0, step: 100000, det_precision = 0.8404461380698578 Global epoch: 0, step: 100000, det_recall = 0.7691042216970202 Global epoch: 0, step: 100000, eval_cor_loss = 0.012904966017094828 Global epoch: 0, step: 100000, eval_cor_macbert_loss = 0.025016339413594532 Global epoch: 0, step: 100000, eval_det_loss = 0.0965598131756879 Global epoch: 0, step: 100000, eval_det_macbert_loss = 0.09517909446854075 Global epoch: 0, step: 100000, eval_loss = 0.030496973886745167 Global epoch: 0, step: 100000, global_step = 100000 Global epoch: 0, step: 100000, lr = 2.9395520191585894e-05 Global epoch: 0, step: 100000, train_cor_loss = 0.06163715333004126 Global epoch: 0, step: 100000, train_cor_macbert_loss = 0.07085385445520664 Global epoch: 0, step: 100000, train_det_loss = 0.0805504613107123 Global epoch: 0, step: 100000, train_det_macbert_loss = 0.07932157712988346 Global epoch: 0, step: 100000, train_loss = 0.01707477082339187 Global epoch: 0, step: 110000, cor_acc = 0.7044431610886523 Global epoch: 0, step: 110000, cor_f1 = 0.6744469815036304 Global epoch: 0, step: 110000, cor_precision = 0.704606840843115 Global epoch: 0, step: 110000, cor_recall = 0.6467630566754715 Global epoch: 0, step: 110000, det_acc = 0.8031423883251291 Global epoch: 0, step: 110000, det_f1 = 0.8045256303383954 Global epoch: 0, step: 110000, det_precision = 0.840502334974126 Global epoch: 0, step: 110000, det_recall = 0.771502386579545 Global epoch: 0, step: 110000, eval_cor_loss = 0.012619795534521264 Global epoch: 0, step: 110000, eval_cor_macbert_loss = 0.024858012300435748 Global epoch: 0, step: 110000, eval_det_loss = 0.09652344822638967 Global epoch: 0, step: 110000, eval_det_macbert_loss = 0.09518078488972977 Global epoch: 0, step: 110000, eval_loss = 0.03030588681807147 Global epoch: 0, step: 110000, global_step = 110000 Global epoch: 0, step: 110000, lr = 2.9269450074482478e-05 Global epoch: 0, step: 110000, train_cor_loss = 0.15105974953102716 Global epoch: 0, step: 110000, train_cor_macbert_loss = 0.17426866174962394 Global epoch: 0, step: 110000, train_det_loss = 0.19903961325534048 Global epoch: 0, step: 110000, train_det_macbert_loss = 0.19601727489076703 Global epoch: 0, step: 110000, train_loss = 0.041973461629734386 Global epoch: 0, step: 120000, cor_acc = 0.7112357799594826 Global epoch: 0, step: 120000, cor_f1 = 0.6811396086885827 Global epoch: 0, step: 120000, cor_precision = 0.7092211033220049 Global epoch: 0, step: 120000, cor_recall = 0.6551971824458964 Global epoch: 0, step: 120000, det_acc = 0.8106866870170228 Global epoch: 0, step: 120000, det_f1 = 0.8118055848293055 Global epoch: 0, step: 120000, det_precision = 0.8452740748172207 Global epoch: 0, step: 120000, det_recall = 0.7808865100329023 Global epoch: 0, step: 120000, eval_cor_loss = 0.012196027093427843 Global epoch: 0, step: 120000, eval_cor_macbert_loss = 0.024399582563638163 Global epoch: 0, step: 120000, eval_det_loss = 0.09651307449317055 Global epoch: 0, step: 120000, eval_det_macbert_loss = 0.09515931931706825 Global epoch: 0, step: 120000, eval_loss = 0.029928564616869147 Global epoch: 0, step: 120000, global_step = 120000 Global epoch: 0, step: 120000, lr = 2.913177216740346e-05 Global epoch: 0, step: 120000, train_cor_loss = 0.05026117377308809 Global epoch: 0, step: 120000, train_cor_macbert_loss = 0.0582075721762624 Global epoch: 0, step: 120000, train_det_loss = 0.06707246876516507 Global epoch: 0, step: 120000, train_det_macbert_loss = 0.06606423505653347 Global epoch: 0, step: 120000, train_loss = 0.01402111787806296 Global epoch: 0, step: 130000, cor_acc = 0.7142516660708229 Global epoch: 0, step: 130000, cor_f1 = 0.6855990143260938 Global epoch: 0, step: 130000, cor_precision = 0.7161350560209953 Global epoch: 0, step: 130000, cor_recall = 0.6575605913156309 Global epoch: 0, step: 130000, det_acc = 0.8102558461439742 Global epoch: 0, step: 130000, det_f1 = 0.8121059116275698 Global epoch: 0, step: 130000, det_precision = 0.8482764711819926 Global epoch: 0, step: 130000, det_recall = 0.7788938319662635 Global epoch: 0, step: 130000, eval_cor_loss = 0.012027134827466793 Global epoch: 0, step: 130000, eval_cor_macbert_loss = 0.024245942050246543 Global epoch: 0, step: 130000, eval_det_loss = 0.0965206406789943 Global epoch: 0, step: 130000, eval_det_macbert_loss = 0.09515668979508196 Global epoch: 0, step: 130000, eval_loss = 0.029791858465536638 Global epoch: 0, step: 130000, global_step = 130000 Global epoch: 0, step: 130000, lr = 2.8982598467392964e-05 Global epoch: 0, step: 130000, train_cor_loss = 0.09890422361784601 Global epoch: 0, step: 130000, train_cor_macbert_loss = 0.1148962859562153 Global epoch: 0, step: 130000, train_det_loss = 0.13313193386515457 Global epoch: 0, step: 130000, train_det_macbert_loss = 0.1311357966305583 Global epoch: 0, step: 130000, train_loss = 0.02767132493707034 Global epoch: 0, step: 140000, cor_acc = 0.7152050160877815 Global epoch: 0, step: 140000, cor_f1 = 0.6867561407951379 Global epoch: 0, step: 140000, cor_precision = 0.7159990948178321 Global epoch: 0, step: 140000, cor_recall = 0.659808146809398 Global epoch: 0, step: 140000, det_acc = 0.8107416879795396 Global epoch: 0, step: 140000, det_f1 = 0.8124299099229461 Global epoch: 0, step: 140000, det_precision = 0.8470242136229916 Global epoch: 0, step: 140000, det_recall = 0.780550535242597 Global epoch: 0, step: 140000, eval_cor_loss = 0.011819936465409868 Global epoch: 0, step: 140000, eval_cor_macbert_loss = 0.024126222791552666 Global epoch: 0, step: 140000, eval_det_loss = 0.09649710652722322 Global epoch: 0, step: 140000, eval_det_macbert_loss = 0.09515932236850803 Global epoch: 0, step: 140000, eval_loss = 0.029651350871152244 Global epoch: 0, step: 140000, global_step = 140000 Global epoch: 0, step: 140000, lr = 2.882205032299424e-05 Global epoch: 0, step: 140000, train_cor_loss = 6.657554588236508 Global epoch: 0, step: 140000, train_cor_macbert_loss = 7.7583234802351075 Global epoch: 0, step: 140000, train_det_loss = 9.032835386871222 Global epoch: 0, step: 140000, train_det_macbert_loss = 8.898304774902948 Global epoch: 0, step: 140000, train_loss = 1.8678959792376146 Global epoch: 0, step: 150000, cor_acc = 0.7201276022330391 Global epoch: 0, step: 150000, cor_f1 = 0.6922553488736203 Global epoch: 0, step: 150000, cor_precision = 0.7207669254015825 Global epoch: 0, step: 150000, cor_recall = 0.6659136197228788 Global epoch: 0, step: 150000, det_acc = 0.8151692654621456 Global epoch: 0, step: 150000, det_f1 = 0.8171236217580077 Global epoch: 0, step: 150000, det_precision = 0.8507780856960137 Global epoch: 0, step: 150000, det_recall = 0.7860303999258539 Global epoch: 0, step: 150000, eval_cor_loss = 0.011498880557634256 Global epoch: 0, step: 150000, eval_cor_macbert_loss = 0.02384920084258698 Global epoch: 0, step: 150000, eval_det_loss = 0.09645208910138192 Global epoch: 0, step: 150000, eval_det_macbert_loss = 0.09514246369012812 Global epoch: 0, step: 150000, eval_loss = 0.02939252703027689 Global epoch: 0, step: 150000, global_step = 150000 Global epoch: 0, step: 150000, lr = 2.8650258335536104e-05 Global epoch: 0, step: 150000, train_cor_loss = 0.07297886971860189 Global epoch: 0, step: 150000, train_cor_macbert_loss = 0.08534871022739485 Global epoch: 0, step: 150000, train_det_loss = 0.10024676492045442 Global epoch: 0, step: 150000, train_det_macbert_loss = 0.09875666796887361 Global epoch: 0, step: 150000, train_loss = 0.02055362036191349 Global epoch: 1, step: 160000, cor_acc = 0.7226943138171584 Global epoch: 1, step: 160000, cor_f1 = 0.6949066948826472 Global epoch: 1, step: 160000, cor_precision = 0.7222444388902775 Global epoch: 1, step: 160000, cor_recall = 0.6695630010658511 Global epoch: 1, step: 160000, det_acc = 0.8171126328044074 Global epoch: 1, step: 160000, det_f1 = 0.8187524047710658 Global epoch: 1, step: 160000, det_precision = 0.8509622594351413 Global epoch: 1, step: 160000, det_recall = 0.788891978312248 Global epoch: 1, step: 160000, eval_cor_loss = 0.011378839217309372 Global epoch: 1, step: 160000, eval_cor_macbert_loss = 0.023733609724037374 Global epoch: 1, step: 160000, eval_det_loss = 0.09646649682488619 Global epoch: 1, step: 160000, eval_det_macbert_loss = 0.09514540518196893 Global epoch: 1, step: 160000, eval_loss = 0.02929368445158826 Global epoch: 1, step: 160000, global_step = 160000 Global epoch: 1, step: 160000, lr = 2.8467362252892478e-05 Global epoch: 1, step: 160000, train_cor_loss = 0.07279981771110611 Global epoch: 1, step: 160000, train_cor_macbert_loss = 0.08547143824832969 Global epoch: 1, step: 160000, train_det_loss = 0.10111338448173793 Global epoch: 1, step: 160000, train_det_macbert_loss = 0.09959881956513861 Global epoch: 1, step: 160000, train_loss = 0.02057967540769542 Global epoch: 1, step: 170000, cor_acc = 0.724940186453263 Global epoch: 1, step: 170000, cor_f1 = 0.6984296844940361 Global epoch: 1, step: 170000, cor_precision = 0.7259060234941265 Global epoch: 1, step: 170000, cor_recall = 0.6729575049816952 Global epoch: 1, step: 170000, det_acc = 0.8172134679023549 Global epoch: 1, step: 170000, det_f1 = 0.8194618122354752 Global epoch: 1, step: 170000, det_precision = 0.8516995751062234 Global epoch: 1, step: 170000, det_recall = 0.7895755132304555 Global epoch: 1, step: 170000, eval_cor_loss = 0.011195941653657887 Global epoch: 1, step: 170000, eval_cor_macbert_loss = 0.023546957408960737 Global epoch: 1, step: 170000, eval_det_loss = 0.09643278374057891 Global epoch: 1, step: 170000, eval_det_macbert_loss = 0.09513783649295979 Global epoch: 1, step: 170000, eval_loss = 0.029133529595897472 Global epoch: 1, step: 170000, global_step = 170000 Global epoch: 1, step: 170000, lr = 2.8273510855801483e-05 Global epoch: 1, step: 170000, train_cor_loss = 0.056876361848190615 Global epoch: 1, step: 170000, train_cor_macbert_loss = 0.0669490824461168 Global epoch: 1, step: 170000, train_det_loss = 0.08006804088578412 Global epoch: 1, step: 170000, train_det_macbert_loss = 0.07887705886581516 Global epoch: 1, step: 170000, train_loss = 0.016136674564584213 Global epoch: 1, step: 180000, cor_acc = 0.727552732172813 Global epoch: 1, step: 180000, cor_f1 = 0.6998141598225525 Global epoch: 1, step: 180000, cor_precision = 0.7251223693691455 Global epoch: 1, step: 180000, cor_recall = 0.6762129848463784 Global epoch: 1, step: 180000, det_acc = 0.8217052131745639 Global epoch: 1, step: 180000, det_f1 = 0.822960254181404 Global epoch: 1, step: 180000, det_precision = 0.8527219420081 Global epoch: 1, step: 180000, det_recall = 0.7952059873024699 Global epoch: 1, step: 180000, eval_cor_loss = 0.011118499626529358 Global epoch: 1, step: 180000, eval_cor_macbert_loss = 0.023503395745695092 Global epoch: 1, step: 180000, eval_det_loss = 0.09641340070676328 Global epoch: 1, step: 180000, eval_det_macbert_loss = 0.09514232325181693 Global epoch: 1, step: 180000, eval_loss = 0.029080985802026726 Global epoch: 1, step: 180000, global_step = 180000 Global epoch: 1, step: 180000, lr = 2.8068861836836563e-05 Global epoch: 1, step: 180000, train_cor_loss = 0.13958648121989428 Global epoch: 1, step: 180000, train_cor_macbert_loss = 0.16457691004269231 Global epoch: 1, step: 180000, train_det_loss = 0.19666330760096018 Global epoch: 1, step: 180000, train_det_macbert_loss = 0.19373209340455536 Global epoch: 1, step: 180000, train_loss = 0.039637275301240726 Global epoch: 1, step: 190000, cor_acc = 0.7295419336505056 Global epoch: 1, step: 190000, cor_f1 = 0.7036642150218961 Global epoch: 1, step: 190000, cor_precision = 0.7328941589811155 Global epoch: 1, step: 190000, cor_recall = 0.676676398350248 Global epoch: 1, step: 190000, det_acc = 0.8181484842651413 Global epoch: 1, step: 190000, det_f1 = 0.8201143297733283 Global epoch: 1, step: 190000, det_precision = 0.8541815672250455 Global epoch: 1, step: 190000, det_recall = 0.7886602715603133 Global epoch: 1, step: 190000, eval_cor_loss = 0.010903060865715858 Global epoch: 1, step: 190000, eval_cor_macbert_loss = 0.023263936128704317 Global epoch: 1, step: 190000, eval_det_loss = 0.09641467441092905 Global epoch: 1, step: 190000, eval_det_macbert_loss = 0.0951410443599851 Global epoch: 1, step: 190000, eval_loss = 0.02888765359885512 Global epoch: 1, step: 190000, global_step = 190000 Global epoch: 1, step: 190000, lr = 2.7853581672128093e-05 Global epoch: 1, step: 190000, train_cor_loss = 0.04683585916170361 Global epoch: 1, step: 190000, train_cor_macbert_loss = 0.05540244140347267 Global epoch: 1, step: 190000, train_det_loss = 0.06674624005634341 Global epoch: 1, step: 190000, train_det_macbert_loss = 0.06575411152791157 Global epoch: 1, step: 190000, train_loss = 0.013347201436955197 Global epoch: 1, step: 200000, cor_acc = 0.7328878255369469 Global epoch: 1, step: 200000, cor_f1 = 0.7066579485672124 Global epoch: 1, step: 200000, cor_precision = 0.7327179767872914 Global epoch: 1, step: 200000, cor_recall = 0.6823879697854396 Global epoch: 1, step: 200000, det_acc = 0.8236852478251703 Global epoch: 1, step: 200000, det_f1 = 0.8254920427346838 Global epoch: 1, step: 200000, det_precision = 0.8559344172565215 Global epoch: 1, step: 200000, det_recall = 0.7971407386811251 Global epoch: 1, step: 200000, eval_cor_loss = 0.010775145994730314 Global epoch: 1, step: 200000, eval_cor_macbert_loss = 0.023095504306497042 Global epoch: 1, step: 200000, eval_det_loss = 0.09640558436840589 Global epoch: 1, step: 200000, eval_det_macbert_loss = 0.09513165907701136 Global epoch: 1, step: 200000, eval_loss = 0.028760320613200593 Global epoch: 1, step: 200000, global_step = 200000 Global epoch: 1, step: 200000, lr = 2.762784548593977e-05 Global epoch: 1, step: 200000, train_cor_loss = 0.09198475881652074 Global epoch: 1, step: 200000, train_cor_macbert_loss = 0.10905968452998616 Global epoch: 1, step: 200000, train_det_loss = 0.13198829641368875 Global epoch: 1, step: 200000, train_det_macbert_loss = 0.13002379613189813 Global epoch: 1, step: 200000, train_loss = 0.026273699649060744 Global epoch: 1, step: 210000, cor_acc = 0.7319986433095913 Global epoch: 1, step: 210000, cor_f1 = 0.7062261722931122 Global epoch: 1, step: 210000, cor_precision = 0.7341901927933785 Global epoch: 1, step: 210000, cor_recall = 0.6803141943556236 Global epoch: 1, step: 210000, det_acc = 0.8214027078807212 Global epoch: 1, step: 210000, det_f1 = 0.8235216298452177 Global epoch: 1, step: 210000, det_precision = 0.8561301292790878 Global epoch: 1, step: 210000, det_recall = 0.793305991936605 Global epoch: 1, step: 210000, eval_cor_loss = 0.010823203926493434 Global epoch: 1, step: 210000, eval_cor_macbert_loss = 0.02320010384380363 Global epoch: 1, step: 210000, eval_det_loss = 0.09639553083759429 Global epoch: 1, step: 210000, eval_det_macbert_loss = 0.09513236669431994 Global epoch: 1, step: 210000, eval_loss = 0.02882449911720013 Global epoch: 1, step: 210000, global_step = 210000 Global epoch: 1, step: 210000, lr = 2.7391836908210074e-05 Global epoch: 1, step: 210000, train_cor_loss = 4.1626061178105624 Global epoch: 1, step: 210000, train_cor_macbert_loss = 4.946738100859569 Global epoch: 1, step: 210000, train_det_loss = 6.0154111946940425 Global epoch: 1, step: 210000, train_det_macbert_loss = 5.926361047856851 Global epoch: 1, step: 210000, train_loss = 1.1917760894792992 Global epoch: 1, step: 220000, cor_acc = 0.7350695303834484 Global epoch: 1, step: 220000, cor_f1 = 0.7107131905068277 Global epoch: 1, step: 220000, cor_precision = 0.7388021451877039 Global epoch: 1, step: 220000, cor_recall = 0.6846818666295936 Global epoch: 1, step: 220000, det_acc = 0.8229610684853652 Global epoch: 1, step: 220000, det_f1 = 0.8260166316916102 Global epoch: 1, step: 220000, det_precision = 0.8586626329803858 Global epoch: 1, step: 220000, det_recall = 0.7957620835071134 Global epoch: 1, step: 220000, eval_cor_loss = 0.010604920008174933 Global epoch: 1, step: 220000, eval_cor_macbert_loss = 0.022955855241630196 Global epoch: 1, step: 220000, eval_det_loss = 0.09640389538228913 Global epoch: 1, step: 220000, eval_det_macbert_loss = 0.09512017148526943 Global epoch: 1, step: 220000, eval_loss = 0.028627635476981324 Global epoch: 1, step: 220000, global_step = 220000 Global epoch: 1, step: 220000, lr = 2.7145747925174524e-05 Global epoch: 1, step: 220000, train_cor_loss = 0.06840056341292099 Global epoch: 1, step: 220000, train_cor_macbert_loss = 0.08147669052738754 Global epoch: 1, step: 220000, train_det_loss = 0.09955883868041908 Global epoch: 1, step: 220000, train_det_macbert_loss = 0.09808785245532371 Global epoch: 1, step: 220000, train_loss = 0.019630334294184607 Global epoch: 1, step: 230000, cor_acc = 0.7356470404898753 Global epoch: 1, step: 230000, cor_f1 = 0.710512731245273 Global epoch: 1, step: 230000, cor_precision = 0.737213821279988 Global epoch: 1, step: 230000, cor_recall = 0.685678205662913 Global epoch: 1, step: 230000, det_acc = 0.824574430052526 Global epoch: 1, step: 230000, det_f1 = 0.8269727127576562 Global epoch: 1, step: 230000, det_precision = 0.858050372437159 Global epoch: 1, step: 230000, det_recall = 0.7980675656888642 Global epoch: 1, step: 230000, eval_cor_loss = 0.01050419957456521 Global epoch: 1, step: 230000, eval_cor_macbert_loss = 0.022944335427929216 Global epoch: 1, step: 230000, eval_det_loss = 0.09638155068261851 Global epoch: 1, step: 230000, eval_det_macbert_loss = 0.09512074443732005 Global epoch: 1, step: 230000, eval_loss = 0.028578300483369717 Global epoch: 1, step: 230000, global_step = 230000 Global epoch: 1, step: 230000, lr = 2.6889778723190365e-05 Global epoch: 1, step: 230000, train_cor_loss = 0.2578006691831318 Global epoch: 1, step: 230000, train_cor_macbert_loss = 0.3075883063322331 Global epoch: 1, step: 230000, train_det_loss = 0.3767872259610643 Global epoch: 1, step: 230000, train_det_macbert_loss = 0.3712272955981867 Global epoch: 1, step: 230000, train_loss = 0.07409785320177334 Global epoch: 1, step: 240000, cor_acc = 0.7402762881683763 Global epoch: 1, step: 240000, cor_f1 = 0.7152538713430652 Global epoch: 1, step: 240000, cor_precision = 0.7414637785680536 Global epoch: 1, step: 240000, cor_recall = 0.6908336808934612 Global epoch: 1, step: 240000, det_acc = 0.8274619805846603 Global epoch: 1, step: 240000, det_f1 = 0.8293370437452771 Global epoch: 1, step: 240000, det_precision = 0.8597274377657855 Global epoch: 1, step: 240000, det_recall = 0.8010218267760323 Global epoch: 1, step: 240000, eval_cor_loss = 0.010356034547547455 Global epoch: 1, step: 240000, eval_cor_macbert_loss = 0.02279577775260669 Global epoch: 1, step: 240000, eval_det_loss = 0.09636319712857214 Global epoch: 1, step: 240000, eval_det_macbert_loss = 0.09512118048085666 Global epoch: 1, step: 240000, eval_loss = 0.028450849517629453 Global epoch: 1, step: 240000, global_step = 240000 Global epoch: 1, step: 240000, lr = 2.66241375258907e-05 Global epoch: 1, step: 240000, train_cor_loss = 0.05419656373238055 Global epoch: 1, step: 240000, train_cor_macbert_loss = 0.06477647759757416 Global epoch: 1, step: 240000, train_det_loss = 0.07967899624555667 Global epoch: 1, step: 240000, train_det_macbert_loss = 0.07850455341443632 Global epoch: 1, step: 240000, train_loss = 0.015606827673535082 Global epoch: 1, step: 250000, cor_acc = 0.7389012641054552 Global epoch: 1, step: 250000, cor_f1 = 0.713489262427469 Global epoch: 1, step: 250000, cor_precision = 0.7375887401983823 Global epoch: 1, step: 250000, cor_recall = 0.6909147782566384 Global epoch: 1, step: 250000, det_acc = 0.8273794791408849 Global epoch: 1, step: 250000, det_f1 = 0.8289645271280732 Global epoch: 1, step: 250000, det_precision = 0.8569644049768719 Global epoch: 1, step: 250000, det_recall = 0.8027364567403494 Global epoch: 1, step: 250000, eval_cor_loss = 0.010285966317231483 Global epoch: 1, step: 250000, eval_cor_macbert_loss = 0.022741551964500895 Global epoch: 1, step: 250000, eval_det_loss = 0.09638339840694803 Global epoch: 1, step: 250000, eval_det_macbert_loss = 0.09511565861989242 Global epoch: 1, step: 250000, eval_loss = 0.028399125507690626 Global epoch: 1, step: 250000, global_step = 250000 Global epoch: 1, step: 250000, lr = 2.6349040424800502e-05 Global epoch: 1, step: 250000, train_cor_loss = 0.13128799304331346 Global epoch: 1, step: 250000, train_cor_macbert_loss = 0.15724153266264357 Global epoch: 1, step: 250000, train_det_loss = 0.19443078477322973 Global epoch: 1, step: 250000, train_det_macbert_loss = 0.1915626989793684 Global epoch: 1, step: 250000, train_loss = 0.0378936410872354 Global epoch: 1, step: 260000, cor_acc = 0.7433013411068027 Global epoch: 1, step: 260000, cor_f1 = 0.7205719778899303 Global epoch: 1, step: 260000, cor_precision = 0.7484149568169337 Global epoch: 1, step: 260000, cor_recall = 0.6947263543259651 Global epoch: 1, step: 260000, det_acc = 0.8269486382678364 Global epoch: 1, step: 260000, det_f1 = 0.8302211006969479 Global epoch: 1, step: 260000, det_precision = 0.8623009335529929 Global epoch: 1, step: 260000, det_recall = 0.8004425598961954 Global epoch: 1, step: 260000, eval_cor_loss = 0.010171158271241711 Global epoch: 1, step: 260000, eval_cor_macbert_loss = 0.022561642561655035 Global epoch: 1, step: 260000, eval_det_loss = 0.09637413430785335 Global epoch: 1, step: 260000, eval_det_macbert_loss = 0.09511304905567655 Global epoch: 1, step: 260000, eval_loss = 0.028272980066167578 Global epoch: 1, step: 260000, global_step = 260000 Global epoch: 1, step: 260000, lr = 2.6064711203552346e-05 Global epoch: 1, step: 260000, train_cor_loss = 0.04451399484747842 Global epoch: 1, step: 260000, train_cor_macbert_loss = 0.053435289474698555 Global epoch: 1, step: 260000, train_det_loss = 0.06647147144805869 Global epoch: 1, step: 260000, train_det_macbert_loss = 0.06549005410432059 Global epoch: 1, step: 260000, train_loss = 0.012881390458654324 Global epoch: 1, step: 270000, cor_acc = 0.7443096920862782 Global epoch: 1, step: 270000, cor_f1 = 0.7203745502224191 Global epoch: 1, step: 270000, cor_precision = 0.745387865346731 Global epoch: 1, step: 270000, cor_recall = 0.6969854951573289 Global epoch: 1, step: 270000, det_acc = 0.8281403257890346 Global epoch: 1, step: 270000, det_f1 = 0.8298778041873469 Global epoch: 1, step: 270000, det_precision = 0.8586933627386601 Global epoch: 1, step: 270000, det_recall = 0.8029334074794939 Global epoch: 1, step: 270000, eval_cor_loss = 0.010027751636797056 Global epoch: 1, step: 270000, eval_cor_macbert_loss = 0.022457239581465862 Global epoch: 1, step: 270000, eval_det_loss = 0.09634721530991823 Global epoch: 1, step: 270000, eval_det_macbert_loss = 0.09510891615898859 Global epoch: 1, step: 270000, eval_loss = 0.028165332095468718 Global epoch: 1, step: 270000, global_step = 270000 Global epoch: 1, step: 270000, lr = 2.5771381155844772e-05 Global epoch: 1, step: 270000, train_cor_loss = 0.08741752100427443 Global epoch: 1, step: 270000, train_cor_macbert_loss = 0.10509213935089137 Global epoch: 1, step: 270000, train_det_loss = 0.13097692325070429 Global epoch: 1, step: 270000, train_det_macbert_loss = 0.12904619290940814 Global epoch: 1, step: 270000, train_loss = 0.025329585620174545 Global epoch: 1, step: 280000, cor_acc = 0.7453547103740982 Global epoch: 1, step: 280000, cor_f1 = 0.7211425839607984 Global epoch: 1, step: 280000, cor_precision = 0.7446929304897314 Global epoch: 1, step: 280000, cor_recall = 0.6990360999119515 Global epoch: 1, step: 280000, det_acc = 0.8315045513296483 Global epoch: 1, step: 280000, det_f1 = 0.8334648021991157 Global epoch: 1, step: 280000, det_precision = 0.8606832543443917 Global epoch: 1, step: 280000, det_recall = 0.8079151026460911 Global epoch: 1, step: 280000, eval_cor_loss = 0.009967041720758508 Global epoch: 1, step: 280000, eval_cor_macbert_loss = 0.022383266444501202 Global epoch: 1, step: 280000, eval_det_loss = 0.09635264061913397 Global epoch: 1, step: 280000, eval_det_macbert_loss = 0.09510451698540873 Global epoch: 1, step: 280000, eval_loss = 0.02810816874449657 Global epoch: 1, step: 280000, global_step = 280000 Global epoch: 1, step: 280000, lr = 2.546928889729154e-05 Global epoch: 1, step: 280000, train_cor_loss = 3.007063632265742 Global epoch: 1, step: 280000, train_cor_macbert_loss = 3.6179019220200326 Global epoch: 1, step: 280000, train_det_loss = 4.508327027550459 Global epoch: 1, step: 280000, train_det_macbert_loss = 4.441652831952581 Global epoch: 1, step: 280000, train_loss = 0.8717147392328531 Global epoch: 1, step: 290000, cor_acc = 0.7482330940791464 Global epoch: 1, step: 290000, cor_f1 = 0.725034298072718 Global epoch: 1, step: 290000, cor_precision = 0.7507288810590177 Global epoch: 1, step: 290000, cor_recall = 0.701040363316187 Global epoch: 1, step: 290000, det_acc = 0.8320545609548167 Global epoch: 1, step: 290000, det_f1 = 0.8345964210185779 Global epoch: 1, step: 290000, det_precision = 0.864173790057442 Global epoch: 1, step: 290000, det_recall = 0.8069766903007554 Global epoch: 1, step: 290000, eval_cor_loss = 0.009865813905509852 Global epoch: 1, step: 290000, eval_cor_macbert_loss = 0.022301662733493856 Global epoch: 1, step: 290000, eval_det_loss = 0.09634141018928163 Global epoch: 1, step: 290000, eval_det_macbert_loss = 0.0951125759208737 Global epoch: 1, step: 290000, eval_loss = 0.028030227498421392 Global epoch: 1, step: 290000, global_step = 290000 Global epoch: 1, step: 290000, lr = 2.5158680171314588e-05 Global epoch: 1, step: 290000, train_cor_loss = 0.06529808740747618 Global epoch: 1, step: 290000, train_cor_macbert_loss = 0.07872386197774518 Global epoch: 1, step: 290000, train_det_loss = 0.09890218203844327 Global epoch: 1, step: 290000, train_det_macbert_loss = 0.09744483207970234 Global epoch: 1, step: 290000, train_loss = 0.018983839218894318 Global epoch: 1, step: 300000, cor_acc = 0.7495989513149813 Global epoch: 1, step: 300000, cor_f1 = 0.7262849279004367 Global epoch: 1, step: 300000, cor_precision = 0.751008488628208 Global epoch: 1, step: 300000, cor_recall = 0.7031373094211966 Global epoch: 1, step: 300000, det_acc = 0.8340345956054231 Global epoch: 1, step: 300000, det_f1 = 0.8365105008077545 Global epoch: 1, step: 300000, det_precision = 0.8649862647561066 Global epoch: 1, step: 300000, det_recall = 0.8098498540247463 Global epoch: 1, step: 300000, eval_cor_loss = 0.009761649020671068 Global epoch: 1, step: 300000, eval_cor_macbert_loss = 0.022171205920731085 Global epoch: 1, step: 300000, eval_det_loss = 0.09634092482250829 Global epoch: 1, step: 300000, eval_det_macbert_loss = 0.09510113781182097 Global epoch: 1, step: 300000, eval_loss = 0.027929618992883418 Global epoch: 1, step: 300000, global_step = 300000 Global epoch: 1, step: 300000, lr = 2.4839807649238806e-05 Global epoch: 1, step: 300000, train_cor_loss = 0.24216672306370424 Global epoch: 1, step: 300000, train_cor_macbert_loss = 0.29246104266514517 Global epoch: 1, step: 300000, train_det_loss = 0.3688077291473525 Global epoch: 1, step: 300000, train_det_macbert_loss = 0.3633707039455276 Global epoch: 1, step: 300000, train_loss = 0.07053254789748385 Global epoch: 1, step: 310000, cor_acc = 0.7516339869281046 Global epoch: 1, step: 310000, cor_f1 = 0.7283430649947352 Global epoch: 1, step: 310000, cor_precision = 0.7530308278489781 Global epoch: 1, step: 310000, cor_recall = 0.7052226701886093 Global epoch: 1, step: 310000, det_acc = 0.83513461485576 Global epoch: 1, step: 310000, det_f1 = 0.8373336843112855 Global epoch: 1, step: 310000, det_precision = 0.8657157702013955 Global epoch: 1, step: 310000, det_recall = 0.8107535103572918 Global epoch: 1, step: 310000, eval_cor_loss = 0.009699390900356254 Global epoch: 1, step: 310000, eval_cor_macbert_loss = 0.022145896902396878 Global epoch: 1, step: 310000, eval_det_loss = 0.09632270389360195 Global epoch: 1, step: 310000, eval_det_macbert_loss = 0.09510178586380183 Global epoch: 1, step: 310000, eval_loss = 0.02789108500068085 Global epoch: 1, step: 310000, global_step = 310000 Global epoch: 1, step: 310000, lr = 2.4512930724751123e-05 Global epoch: 1, step: 310000, train_cor_loss = 0.05231073170881335 Global epoch: 1, step: 310000, train_cor_macbert_loss = 0.06316140636988234 Global epoch: 1, step: 310000, train_det_loss = 0.079293555029164 Global epoch: 1, step: 310000, train_det_macbert_loss = 0.07812491081665923 Global epoch: 1, step: 310000, train_loss = 0.015220511376989999 Global epoch: 2, step: 320000, cor_acc = 0.7507081373924044 Global epoch: 2, step: 320000, cor_f1 = 0.7273878274995074 Global epoch: 2, step: 320000, cor_precision = 0.7506502150948513 Global epoch: 2, step: 320000, cor_recall = 0.7055238889661245 Global epoch: 2, step: 320000, det_acc = 0.8336954230032358 Global epoch: 2, step: 320000, det_f1 = 0.835520147154554 Global epoch: 2, step: 320000, det_precision = 0.8622406843590913 Global epoch: 2, step: 320000, det_recall = 0.8104059502293897 Global epoch: 2, step: 320000, eval_cor_loss = 0.009663314078689441 Global epoch: 2, step: 320000, eval_cor_macbert_loss = 0.022047542536599008 Global epoch: 2, step: 320000, eval_det_loss = 0.09632609675170668 Global epoch: 2, step: 320000, eval_det_macbert_loss = 0.09509600701787471 Global epoch: 2, step: 320000, eval_loss = 0.0278337727707918 Global epoch: 2, step: 320000, global_step = 320000 Global epoch: 2, step: 320000, lr = 2.4178315302891145e-05 Global epoch: 2, step: 320000, train_cor_loss = 0.06577047293180836 Global epoch: 2, step: 320000, train_cor_macbert_loss = 0.07962380214078282 Global epoch: 2, step: 320000, train_det_loss = 0.10098882471633293 Global epoch: 2, step: 320000, train_det_macbert_loss = 0.09949397892845115 Global epoch: 2, step: 320000, train_loss = 0.01920719488403052 Global epoch: 2, step: 330000, cor_acc = 0.7536965230224862 Global epoch: 2, step: 330000, cor_f1 = 0.7315020945541592 Global epoch: 2, step: 330000, cor_precision = 0.7565483264012676 Global epoch: 2, step: 330000, cor_recall = 0.70806107789981 Global epoch: 2, step: 330000, det_acc = 0.8352904509162243 Global epoch: 2, step: 330000, det_f1 = 0.8380371035308198 Global epoch: 2, step: 330000, det_precision = 0.8667310358486829 Global epoch: 2, step: 330000, det_recall = 0.811182167848371 Global epoch: 2, step: 330000, eval_cor_loss = 0.009585512544003751 Global epoch: 2, step: 330000, eval_cor_macbert_loss = 0.02195773007770292 Global epoch: 2, step: 330000, eval_det_loss = 0.0963166621039949 Global epoch: 2, step: 330000, eval_det_macbert_loss = 0.09509841262271977 Global epoch: 2, step: 330000, eval_loss = 0.027762009644003355 Global epoch: 2, step: 330000, global_step = 330000 Global epoch: 2, step: 330000, lr = 2.3836233583745025e-05 Global epoch: 2, step: 330000, train_cor_loss = 0.04300015114120329 Global epoch: 2, step: 330000, train_cor_macbert_loss = 0.05209843507375378 Global epoch: 2, step: 330000, train_det_loss = 0.06619950398197591 Global epoch: 2, step: 330000, train_det_macbert_loss = 0.06522148838149508 Global epoch: 2, step: 330000, train_loss = 0.012568368772942222 Global epoch: 2, step: 340000, cor_acc = 0.7561348990273996 Global epoch: 2, step: 340000, cor_f1 = 0.7332234996358773 Global epoch: 2, step: 340000, cor_precision = 0.7562738578992735 Global epoch: 2, step: 340000, cor_recall = 0.7115366791788312 Global epoch: 2, step: 340000, det_acc = 0.8367113091145761 Global epoch: 2, step: 340000, det_f1 = 0.838162434487781 Global epoch: 2, step: 340000, det_precision = 0.8645117596355129 Global epoch: 2, step: 340000, det_recall = 0.8133717966541545 Global epoch: 2, step: 340000, eval_cor_loss = 0.009472542753871719 Global epoch: 2, step: 340000, eval_cor_macbert_loss = 0.02189211841542694 Global epoch: 2, step: 340000, eval_det_loss = 0.0963025502369083 Global epoch: 2, step: 340000, eval_det_macbert_loss = 0.09510461673494379 Global epoch: 2, step: 340000, eval_loss = 0.027685519436724336 Global epoch: 2, step: 340000, global_step = 340000 Global epoch: 2, step: 340000, lr = 2.348696384101845e-05 Global epoch: 2, step: 340000, train_cor_loss = 0.08405975450479493 Global epoch: 2, step: 340000, train_cor_macbert_loss = 0.10199336844720157 Global epoch: 2, step: 340000, train_det_loss = 0.13001706011156322 Global epoch: 2, step: 340000, train_det_macbert_loss = 0.1280855455332888 Global epoch: 2, step: 340000, train_loss = 0.024607568921736538 Global epoch: 2, step: 350000, cor_acc = 0.7559148951773322 Global epoch: 2, step: 350000, cor_f1 = 0.7328875888006687 Global epoch: 2, step: 350000, cor_precision = 0.7560041382368156 Global epoch: 2, step: 350000, cor_recall = 0.7111427777005422 Global epoch: 2, step: 350000, det_acc = 0.8387463447276994 Global epoch: 2, step: 350000, det_f1 = 0.8407736851531252 Global epoch: 2, step: 350000, det_precision = 0.8672931497401286 Global epoch: 2, step: 350000, det_recall = 0.8158278882246629 Global epoch: 2, step: 350000, eval_cor_loss = 0.009445478919457262 Global epoch: 2, step: 350000, eval_cor_macbert_loss = 0.021929622153805887 Global epoch: 2, step: 350000, eval_det_loss = 0.09629790271282615 Global epoch: 2, step: 350000, eval_det_macbert_loss = 0.09510104350551277 Global epoch: 2, step: 350000, eval_loss = 0.027689339856804728 Global epoch: 2, step: 350000, global_step = 350000 Global epoch: 2, step: 350000, lr = 2.3130790195668936e-05 Global epoch: 2, step: 350000, train_cor_loss = 2.324046062372874 Global epoch: 2, step: 350000, train_cor_macbert_loss = 2.8224887096776032 Global epoch: 2, step: 350000, train_det_loss = 3.6044090798817137 Global epoch: 2, step: 350000, train_det_macbert_loss = 3.5510778231407323 Global epoch: 2, step: 350000, train_loss = 0.6809847198056176 Global epoch: 2, step: 360000, cor_acc = 0.7558782278689877 Global epoch: 2, step: 360000, cor_f1 = 0.7331229229933953 Global epoch: 2, step: 360000, cor_precision = 0.7557723297208861 Global epoch: 2, step: 360000, cor_recall = 0.7117915566059595 Global epoch: 2, step: 360000, det_acc = 0.8389388480965083 Global epoch: 2, step: 360000, det_f1 = 0.8412436086367677 Global epoch: 2, step: 360000, det_precision = 0.867233341124082 Global epoch: 2, step: 360000, det_recall = 0.8167663005699987 Global epoch: 2, step: 360000, eval_cor_loss = 0.009445360503432669 Global epoch: 2, step: 360000, eval_cor_macbert_loss = 0.02187875737344649 Global epoch: 2, step: 360000, eval_det_loss = 0.09629014957880772 Global epoch: 2, step: 360000, eval_det_macbert_loss = 0.09509671813876913 Global epoch: 2, step: 360000, eval_loss = 0.027666766105295625 Global epoch: 2, step: 360000, global_step = 360000 Global epoch: 2, step: 360000, lr = 2.276800238478155e-05 Global epoch: 2, step: 360000, train_cor_loss = 0.0630651328185919 Global epoch: 2, step: 360000, train_cor_macbert_loss = 0.0767024099278562 Global epoch: 2, step: 360000, train_det_loss = 0.09828001729562116 Global epoch: 2, step: 360000, train_det_macbert_loss = 0.09682175490272683 Global epoch: 2, step: 360000, train_loss = 0.0185084602140798 Global epoch: 2, step: 370000, cor_acc = 0.7576932596320436 Global epoch: 2, step: 370000, cor_f1 = 0.7355308295796916 Global epoch: 2, step: 370000, cor_precision = 0.7582258084355281 Global epoch: 2, step: 370000, cor_recall = 0.714154965475694 Global epoch: 2, step: 370000, det_acc = 0.8393330216612124 Global epoch: 2, step: 370000, det_f1 = 0.8417981684216806 Global epoch: 2, step: 370000, det_precision = 0.8677720513167444 Global epoch: 2, step: 370000, det_recall = 0.8173339821122387 Global epoch: 2, step: 370000, eval_cor_loss = 0.009384506407576907 Global epoch: 2, step: 370000, eval_cor_macbert_loss = 0.021791835070340052 Global epoch: 2, step: 370000, eval_det_loss = 0.09629786312492737 Global epoch: 2, step: 370000, eval_det_macbert_loss = 0.09509792503890177 Global epoch: 2, step: 370000, eval_loss = 0.02760463018692228 Global epoch: 2, step: 370000, global_step = 370000 Global epoch: 2, step: 370000, lr = 2.2398895525876065e-05 Global epoch: 2, step: 370000, train_cor_loss = 0.2301772188387975 Global epoch: 2, step: 370000, train_cor_macbert_loss = 0.2804008463007911 Global epoch: 2, step: 370000, train_det_loss = 0.3613539915176073 Global epoch: 2, step: 370000, train_det_macbert_loss = 0.3560082389404204 Global epoch: 2, step: 370000, train_loss = 0.06769946331500858 Global epoch: 2, step: 380000, cor_acc = 0.7591507851387399 Global epoch: 2, step: 380000, cor_f1 = 0.7381828847109244 Global epoch: 2, step: 380000, cor_precision = 0.7636190263897661 Global epoch: 2, step: 380000, cor_recall = 0.7143866722276287 Global epoch: 2, step: 380000, det_acc = 0.8380496658691527 Global epoch: 2, step: 380000, det_f1 = 0.8412193910227633 Global epoch: 2, step: 380000, det_precision = 0.870205941722084 Global epoch: 2, step: 380000, det_recall = 0.8141016729227489 Global epoch: 2, step: 380000, eval_cor_loss = 0.009301613045211175 Global epoch: 2, step: 380000, eval_cor_macbert_loss = 0.021735749596238956 Global epoch: 2, step: 380000, eval_det_loss = 0.09627714147668401 Global epoch: 2, step: 380000, eval_det_macbert_loss = 0.09509480375456901 Global epoch: 2, step: 380000, eval_loss = 0.027543775942607977 Global epoch: 2, step: 380000, global_step = 380000 Global epoch: 2, step: 380000, lr = 2.202376987683728e-05 Global epoch: 2, step: 380000, train_cor_loss = 0.05040457773334355 Global epoch: 2, step: 380000, train_cor_macbert_loss = 0.06140610928687472 Global epoch: 2, step: 380000, train_det_loss = 0.07892570719285147 Global epoch: 2, step: 380000, train_det_macbert_loss = 0.07775911038130583 Global epoch: 2, step: 380000, train_loss = 0.014817726278721835 Global epoch: 2, step: 390000, cor_acc = 0.7590224495595339 Global epoch: 2, step: 390000, cor_f1 = 0.7375661059487885 Global epoch: 2, step: 390000, cor_precision = 0.7616285527403769 Global epoch: 2, step: 390000, cor_recall = 0.7149775244450624 Global epoch: 2, step: 390000, det_acc = 0.8386638432839242 Global epoch: 2, step: 390000, det_f1 = 0.841399504018644 Global epoch: 2, step: 390000, det_precision = 0.868849424280196 Global epoch: 2, step: 390000, det_recall = 0.8156309374855183 Global epoch: 2, step: 390000, eval_cor_loss = 0.009277084522634337 Global epoch: 2, step: 390000, eval_cor_macbert_loss = 0.021669470442159194 Global epoch: 2, step: 390000, eval_det_loss = 0.09628672641381181 Global epoch: 2, step: 390000, eval_det_macbert_loss = 0.0950937189142119 Global epoch: 2, step: 390000, eval_loss = 0.027505820187322557 Global epoch: 2, step: 390000, global_step = 390000 Global epoch: 2, step: 390000, lr = 2.1642930591663838e-05 Global epoch: 2, step: 390000, train_cor_loss = 0.12076272348296739 Global epoch: 2, step: 390000, train_cor_macbert_loss = 0.14728952084405456 Global epoch: 2, step: 390000, train_det_loss = 0.1902081164747222 Global epoch: 2, step: 390000, train_det_macbert_loss = 0.18739343460895128 Global epoch: 2, step: 390000, train_loss = 0.03556058114577117 Global epoch: 2, step: 400000, cor_acc = 0.7614791592186196 Global epoch: 2, step: 400000, cor_f1 = 0.7399332166516335 Global epoch: 2, step: 400000, cor_precision = 0.7637715652785143 Global epoch: 2, step: 400000, cor_recall = 0.7175378840539414 Global epoch: 2, step: 400000, det_acc = 0.840084701482276 Global epoch: 2, step: 400000, det_f1 = 0.8423781562300262 Global epoch: 2, step: 400000, det_precision = 0.86951696242493 Global epoch: 2, step: 400000, det_recall = 0.816882153945966 Global epoch: 2, step: 400000, eval_cor_loss = 0.00917305684590366 Global epoch: 2, step: 400000, eval_cor_macbert_loss = 0.021532240935593923 Global epoch: 2, step: 400000, eval_det_loss = 0.0962857376315558 Global epoch: 2, step: 400000, eval_det_macbert_loss = 0.09508781285142312 Global epoch: 2, step: 400000, eval_loss = 0.027402768757415985 Global epoch: 2, step: 400000, global_step = 400000 Global epoch: 2, step: 400000, lr = 2.1256687472234126e-05 Global epoch: 2, step: 400000, train_cor_loss = 0.04163534006508831 Global epoch: 2, step: 400000, train_cor_macbert_loss = 0.05086090866798572 Global epoch: 2, step: 400000, train_det_loss = 0.06594210875004258 Global epoch: 2, step: 400000, train_det_macbert_loss = 0.06496355035577545 Global epoch: 2, step: 400000, train_loss = 0.012282207912474906 Global epoch: 2, step: 410000, cor_acc = 0.7608374813225898 Global epoch: 2, step: 410000, cor_f1 = 0.7399420912808572 Global epoch: 2, step: 410000, cor_precision = 0.7633053738806981 Global epoch: 2, step: 410000, cor_recall = 0.7179665415450206 Global epoch: 2, step: 410000, det_acc = 0.8401855365802234 Global epoch: 2, step: 410000, det_f1 = 0.8432942300229843 Global epoch: 2, step: 410000, det_precision = 0.8699208020790994 Global epoch: 2, step: 410000, det_recall = 0.818249223782381 Global epoch: 2, step: 410000, eval_cor_loss = 0.009116549482755188 Global epoch: 2, step: 410000, eval_cor_macbert_loss = 0.021479869042136862 Global epoch: 2, step: 410000, eval_det_loss = 0.096286606540501 Global epoch: 2, step: 410000, eval_det_macbert_loss = 0.09507715935119608 Global epoch: 2, step: 410000, eval_loss = 0.027355761220555823 Global epoch: 2, step: 410000, global_step = 410000 Global epoch: 2, step: 410000, lr = 2.0865354716291334e-05 Global epoch: 2, step: 410000, train_cor_loss = 0.08132548765737965 Global epoch: 2, step: 410000, train_cor_macbert_loss = 0.09940760045269494 Global epoch: 2, step: 410000, train_det_loss = 0.12906842721815617 Global epoch: 2, step: 410000, train_det_macbert_loss = 0.1271524054120765 Global epoch: 2, step: 410000, train_loss = 0.024007031957315954 Global epoch: 2, step: 420000, cor_acc = 0.7621300039417357 Global epoch: 2, step: 420000, cor_f1 = 0.7404462484302745 Global epoch: 2, step: 420000, cor_precision = 0.7613301185944901 Global epoch: 2, step: 420000, cor_recall = 0.7206775105426572 Global epoch: 2, step: 420000, det_acc = 0.8421472375766575 Global epoch: 2, step: 420000, det_f1 = 0.8443486903578677 Global epoch: 2, step: 420000, det_precision = 0.8681630704835571 Global epoch: 2, step: 420000, det_recall = 0.8218059224245795 Global epoch: 2, step: 420000, eval_cor_loss = 0.00903933019517836 Global epoch: 2, step: 420000, eval_cor_macbert_loss = 0.02141987445961648 Global epoch: 2, step: 420000, eval_det_loss = 0.09627973033392126 Global epoch: 2, step: 420000, eval_det_macbert_loss = 0.09507366104258431 Global epoch: 2, step: 420000, eval_loss = 0.02729666723269883 Global epoch: 2, step: 420000, global_step = 420000 Global epoch: 2, step: 420000, lr = 2.0469250661852538e-05 Global epoch: 2, step: 420000, train_cor_loss = 1.8788728870921825 Global epoch: 2, step: 420000, train_cor_macbert_loss = 2.300393274537768 Global epoch: 2, step: 420000, train_det_loss = 3.003914569482705 Global epoch: 2, step: 420000, train_det_macbert_loss = 2.9592223867683325 Global epoch: 2, step: 420000, train_loss = 0.5558558645919317 Global epoch: 2, step: 430000, cor_acc = 0.7637616991630687 Global epoch: 2, step: 430000, cor_f1 = 0.7427970632687563 Global epoch: 2, step: 430000, cor_precision = 0.7667764334431001 Global epoch: 2, step: 430000, cor_recall = 0.7202720237267713 Global epoch: 2, step: 430000, det_acc = 0.8418997332453317 Global epoch: 2, step: 430000, det_f1 = 0.844638792809907 Global epoch: 2, step: 430000, det_precision = 0.8719058719058719 Global epoch: 2, step: 430000, det_recall = 0.8190254414013625 Global epoch: 2, step: 430000, eval_cor_loss = 0.009024267032320251 Global epoch: 2, step: 430000, eval_cor_macbert_loss = 0.02142701476044588 Global epoch: 2, step: 430000, eval_det_loss = 0.0962567185681085 Global epoch: 2, step: 430000, eval_det_macbert_loss = 0.0950815334077351 Global epoch: 2, step: 430000, eval_loss = 0.027292164566273286 Global epoch: 2, step: 430000, global_step = 430000 Global epoch: 2, step: 430000, lr = 2.0068697528249843e-05 Global epoch: 2, step: 430000, train_cor_loss = 0.06113502322133728 Global epoch: 2, step: 430000, train_cor_macbert_loss = 0.07487749514055737 Global epoch: 2, step: 430000, train_det_loss = 0.0977004259534295 Global epoch: 2, step: 430000, train_det_macbert_loss = 0.09624679241464207 Global epoch: 2, step: 430000, train_loss = 0.018087840973071416 Global epoch: 2, step: 440000, cor_acc = 0.7655492304448661 Global epoch: 2, step: 440000, cor_f1 = 0.7444107752141443 Global epoch: 2, step: 440000, cor_precision = 0.7672388353334645 Global epoch: 2, step: 440000, cor_recall = 0.7229018953612308 Global epoch: 2, step: 440000, det_acc = 0.8440356039564025 Global epoch: 2, step: 440000, det_f1 = 0.8465557968075207 Global epoch: 2, step: 440000, det_precision = 0.8725162305724966 Global epoch: 2, step: 440000, det_recall = 0.8220955558644979 Global epoch: 2, step: 440000, eval_cor_loss = 0.008944376365802661 Global epoch: 2, step: 440000, eval_cor_macbert_loss = 0.021319448146002534 Global epoch: 2, step: 440000, eval_det_loss = 0.09626876682095498 Global epoch: 2, step: 440000, eval_det_macbert_loss = 0.0950664088579959 Global epoch: 2, step: 440000, eval_loss = 0.027212264501180895 Global epoch: 2, step: 440000, global_step = 440000 Global epoch: 2, step: 440000, lr = 1.9664021154014135e-05 Global epoch: 2, step: 440000, train_cor_loss = 0.22100952554362666 Global epoch: 2, step: 440000, train_cor_macbert_loss = 0.27082226471070336 Global epoch: 2, step: 440000, train_det_loss = 0.35409925217573324 Global epoch: 2, step: 440000, train_det_macbert_loss = 0.34885253908982217 Global epoch: 2, step: 440000, train_loss = 0.06543747581037959 Global epoch: 2, step: 450000, cor_acc = 0.7664109121909634 Global epoch: 2, step: 450000, cor_f1 = 0.7448554295553048 Global epoch: 2, step: 450000, cor_precision = 0.7639135835545705 Global epoch: 2, step: 450000, cor_recall = 0.7267250567681542 Global epoch: 2, step: 450000, det_acc = 0.8457314669673386 Global epoch: 2, step: 450000, det_f1 = 0.8476043460191177 Global epoch: 2, step: 450000, det_precision = 0.8692914728304553 Global epoch: 2, step: 450000, det_recall = 0.8269729829927244 Global epoch: 2, step: 450000, eval_cor_loss = 0.008921995054771849 Global epoch: 2, step: 450000, eval_cor_macbert_loss = 0.021323218161354348 Global epoch: 2, step: 450000, eval_det_loss = 0.09625421721096158 Global epoch: 2, step: 450000, eval_det_macbert_loss = 0.09507526614577914 Global epoch: 2, step: 450000, eval_loss = 0.027203927794594247 Global epoch: 2, step: 450000, global_step = 450000 Global epoch: 2, step: 450000, lr = 1.925555073181477e-05 Global epoch: 2, step: 450000, train_cor_loss = 0.048787140106903326 Global epoch: 2, step: 450000, train_cor_macbert_loss = 0.05986488338176629 Global epoch: 2, step: 450000, train_det_loss = 0.07856978459654985 Global epoch: 2, step: 450000, train_det_macbert_loss = 0.07740183370458995 Global epoch: 2, step: 450000, train_loss = 0.014468745779228598 Global epoch: 2, step: 460000, cor_acc = 0.7666217492139445 Global epoch: 2, step: 460000, cor_f1 = 0.7451939964397769 Global epoch: 2, step: 460000, cor_precision = 0.7664817332304564 Global epoch: 2, step: 460000, cor_recall = 0.725056768154224 Global epoch: 2, step: 460000, det_acc = 0.8456764660048217 Global epoch: 2, step: 460000, det_f1 = 0.847880833735198 Global epoch: 2, step: 460000, det_precision = 0.8721019950766066 Global epoch: 2, step: 460000, det_recall = 0.8249687195884888 Global epoch: 2, step: 460000, eval_cor_loss = 0.008940416319459995 Global epoch: 2, step: 460000, eval_cor_macbert_loss = 0.021360846162628688 Global epoch: 2, step: 460000, eval_det_loss = 0.09626875333302323 Global epoch: 2, step: 460000, eval_det_macbert_loss = 0.09508105553959653 Global epoch: 2, step: 460000, eval_loss = 0.02722927312331443 Global epoch: 2, step: 460000, global_step = 460000 Global epoch: 2, step: 460000, lr = 1.8843618540670732e-05 Global epoch: 2, step: 460000, train_cor_loss = 0.11693768903653778 Global epoch: 2, step: 460000, train_cor_macbert_loss = 0.14348349539271008 Global epoch: 2, step: 460000, train_det_loss = 0.18810158887687004 Global epoch: 2, step: 460000, train_det_macbert_loss = 0.18531508884651132 Global epoch: 2, step: 460000, train_loss = 0.03467131461899906 Global epoch: 2, step: 470000, cor_acc = 0.7660717395887762 Global epoch: 2, step: 470000, cor_f1 = 0.7442490494296579 Global epoch: 2, step: 470000, cor_precision = 0.7638163992000391 Global epoch: 2, step: 470000, cor_recall = 0.7256592057092544 Global epoch: 2, step: 470000, det_acc = 0.8465839818863496 Global epoch: 2, step: 470000, det_f1 = 0.8486097908745246 Global epoch: 2, step: 470000, det_precision = 0.8709209306863079 Global epoch: 2, step: 470000, det_recall = 0.8274132258214004 Global epoch: 2, step: 470000, eval_cor_loss = 0.00889328042624343 Global epoch: 2, step: 470000, eval_cor_macbert_loss = 0.021256705621277627 Global epoch: 2, step: 470000, eval_det_loss = 0.09625880076839091 Global epoch: 2, step: 470000, eval_det_macbert_loss = 0.0950749024412423 Global epoch: 2, step: 470000, eval_loss = 0.02716377274794283 Global epoch: 2, step: 470000, global_step = 470000 Global epoch: 2, step: 470000, lr = 1.8428559675651138e-05 Global epoch: 2, step: 470000, train_cor_loss = 0.04038391904963965 Global epoch: 2, step: 470000, train_cor_macbert_loss = 0.049662744631874416 Global epoch: 2, step: 470000, train_det_loss = 0.06567810136792988 Global epoch: 2, step: 470000, train_det_macbert_loss = 0.06470090979496716 Global epoch: 2, step: 470000, train_loss = 0.012012064840200993 Global epoch: 3, step: 480000, cor_acc = 0.7683726131873975 Global epoch: 3, step: 480000, cor_f1 = 0.7471348538701055 Global epoch: 3, step: 480000, cor_precision = 0.7684780345617322 Global epoch: 3, step: 480000, cor_recall = 0.7269451781824923 Global epoch: 3, step: 480000, det_acc = 0.8463548112091962 Global epoch: 3, step: 480000, det_f1 = 0.8484285603719779 Global epoch: 3, step: 480000, det_precision = 0.872665368458439 Global epoch: 3, step: 480000, det_recall = 0.8255016451179388 Global epoch: 3, step: 480000, eval_cor_loss = 0.008868916550665117 Global epoch: 3, step: 480000, eval_cor_macbert_loss = 0.021254451602765085 Global epoch: 3, step: 480000, eval_det_loss = 0.09625028338085623 Global epoch: 3, step: 480000, eval_det_macbert_loss = 0.09507437557750907 Global epoch: 3, step: 480000, eval_loss = 0.02715178181552985 Global epoch: 3, step: 480000, global_step = 480000 Global epoch: 3, step: 480000, lr = 1.8010711775284974e-05 Global epoch: 3, step: 480000, train_cor_loss = 0.06211216998396547 Global epoch: 3, step: 480000, train_cor_macbert_loss = 0.07638126535580063 Global epoch: 3, step: 480000, train_det_loss = 0.10090940414972113 Global epoch: 3, step: 480000, train_det_macbert_loss = 0.0994031778178536 Global epoch: 3, step: 480000, train_loss = 0.01847078898490349 Global epoch: 3, step: 490000, cor_acc = 0.7696926362878017 Global epoch: 3, step: 490000, cor_f1 = 0.7491262020304267 Global epoch: 3, step: 490000, cor_precision = 0.7706329858261157 Global epoch: 3, step: 490000, cor_recall = 0.7287872468603735 Global epoch: 3, step: 490000, det_acc = 0.8467214842926418 Global epoch: 3, step: 490000, det_f1 = 0.8491946768287237 Global epoch: 3, step: 490000, det_precision = 0.8735743424518247 Global epoch: 3, step: 490000, det_recall = 0.8261388386857593 Global epoch: 3, step: 490000, eval_cor_loss = 0.008825239511573296 Global epoch: 3, step: 490000, eval_cor_macbert_loss = 0.02117059741860539 Global epoch: 3, step: 490000, eval_det_loss = 0.09626338218304112 Global epoch: 3, step: 490000, eval_det_macbert_loss = 0.09507290893148307 Global epoch: 3, step: 490000, eval_loss = 0.027098453434130133 Global epoch: 3, step: 490000, global_step = 490000 Global epoch: 3, step: 490000, lr = 1.7590414746901813e-05 Global epoch: 3, step: 490000, train_cor_loss = 1.5809493912906618 Global epoch: 3, step: 490000, train_cor_macbert_loss = 1.9451704999879706 Global epoch: 3, step: 490000, train_det_loss = 2.573835046809655 Global epoch: 3, step: 490000, train_det_macbert_loss = 2.5355231122013158 Global epoch: 3, step: 490000, train_loss = 0.4704507185222568 Global epoch: 3, step: 500000, cor_acc = 0.7709026574631723 Global epoch: 3, step: 500000, cor_f1 = 0.7514270887389725 Global epoch: 3, step: 500000, cor_precision = 0.7744457969090037 Global epoch: 3, step: 500000, cor_recall = 0.729737244543306 Global epoch: 3, step: 500000, det_acc = 0.8457039664860801 Global epoch: 3, step: 500000, det_f1 = 0.848773329993021 Global epoch: 3, step: 500000, det_precision = 0.8747740769429383 Global epoch: 3, step: 500000, det_recall = 0.8242735993326845 Global epoch: 3, step: 500000, eval_cor_loss = 0.008753290434465018 Global epoch: 3, step: 500000, eval_cor_macbert_loss = 0.021095911799393522 Global epoch: 3, step: 500000, eval_det_loss = 0.09623559890028249 Global epoch: 3, step: 500000, eval_det_macbert_loss = 0.09507351143466382 Global epoch: 3, step: 500000, eval_loss = 0.02703409514200719 Global epoch: 3, step: 500000, global_step = 500000 Global epoch: 3, step: 500000, lr = 1.7168010490126894e-05 Global epoch: 3, step: 500000, train_cor_loss = 0.05925393202650859 Global epoch: 3, step: 500000, train_cor_macbert_loss = 0.07303167905173662 Global epoch: 3, step: 500000, train_det_loss = 0.09714203361469673 Global epoch: 3, step: 500000, train_det_macbert_loss = 0.09568981346151087 Global epoch: 3, step: 500000, train_loss = 0.017670943856674514 Global epoch: 3, step: 510000, cor_acc = 0.772057677676026 Global epoch: 3, step: 510000, cor_f1 = 0.7519378923340306 Global epoch: 3, step: 510000, cor_precision = 0.7721712164867901 Global epoch: 3, step: 510000, cor_recall = 0.732737846980861 Global epoch: 3, step: 510000, det_acc = 0.8468223193905894 Global epoch: 3, step: 510000, det_f1 = 0.84890384249572 Global epoch: 3, step: 510000, det_precision = 0.8717463495629243 Global epoch: 3, step: 510000, det_recall = 0.8272278604198526 Global epoch: 3, step: 510000, eval_cor_loss = 0.008695448611780569 Global epoch: 3, step: 510000, eval_cor_macbert_loss = 0.021033685376725127 Global epoch: 3, step: 510000, eval_det_loss = 0.09623201298455065 Global epoch: 3, step: 510000, eval_det_macbert_loss = 0.09506728418872559 Global epoch: 3, step: 510000, eval_loss = 0.026982330146230096 Global epoch: 3, step: 510000, global_step = 510000 Global epoch: 3, step: 510000, lr = 1.6743842618755544e-05 Global epoch: 3, step: 510000, train_cor_loss = 0.21124210829284656 Global epoch: 3, step: 510000, train_cor_macbert_loss = 0.2603696000054077 Global epoch: 3, step: 510000, train_det_loss = 0.3471631624781689 Global epoch: 3, step: 510000, train_det_macbert_loss = 0.34198491820602483 Global epoch: 3, step: 510000, train_loss = 0.06303027246433493 Global epoch: 3, step: 520000, cor_acc = 0.7717735060363556 Global epoch: 3, step: 520000, cor_f1 = 0.7519372451777497 Global epoch: 3, step: 520000, cor_precision = 0.7744082113741283 Global epoch: 3, step: 520000, cor_recall = 0.7307335835766254 Global epoch: 3, step: 520000, det_acc = 0.8468406530447616 Global epoch: 3, step: 520000, det_f1 = 0.8495624806275482 Global epoch: 3, step: 520000, det_precision = 0.874950888910716 Global epoch: 3, step: 520000, det_recall = 0.8256059131563094 Global epoch: 3, step: 520000, eval_cor_loss = 0.00870841993615481 Global epoch: 3, step: 520000, eval_cor_macbert_loss = 0.02106267608712012 Global epoch: 3, step: 520000, eval_det_loss = 0.09623053349277134 Global epoch: 3, step: 520000, eval_det_macbert_loss = 0.09507216885358279 Global epoch: 3, step: 520000, eval_loss = 0.027000419369032396 Global epoch: 3, step: 520000, global_step = 520000 Global epoch: 3, step: 520000, lr = 1.63182561812332e-05 Global epoch: 3, step: 520000, train_cor_loss = 0.04737624263201305 Global epoch: 3, step: 520000, train_cor_macbert_loss = 0.05846993988090509 Global epoch: 3, step: 520000, train_det_loss = 0.07816933487755329 Global epoch: 3, step: 520000, train_det_macbert_loss = 0.07699884953544664 Global epoch: 3, step: 520000, train_loss = 0.014155560786294763 Global epoch: 3, step: 530000, cor_acc = 0.7723418493156964 Global epoch: 3, step: 530000, cor_f1 = 0.7523152826487546 Global epoch: 3, step: 530000, cor_precision = 0.7725297262983128 Global epoch: 3, step: 530000, cor_recall = 0.7331317484591501 Global epoch: 3, step: 530000, det_acc = 0.8489215227933156 Global epoch: 3, step: 530000, det_f1 = 0.8516316947036795 Global epoch: 3, step: 530000, det_precision = 0.8745147349659399 Global epoch: 3, step: 530000, det_recall = 0.8299156587422958 Global epoch: 3, step: 530000, eval_cor_loss = 0.00865542357903871 Global epoch: 3, step: 530000, eval_cor_macbert_loss = 0.021030742839706133 Global epoch: 3, step: 530000, eval_det_loss = 0.09623237104053828 Global epoch: 3, step: 530000, eval_det_macbert_loss = 0.09506220593982971 Global epoch: 3, step: 530000, eval_loss = 0.026963714908287518 Global epoch: 3, step: 530000, global_step = 530000 Global epoch: 3, step: 530000, lr = 1.589159737996832e-05 Global epoch: 3, step: 530000, train_cor_loss = 0.11267395290809247 Global epoch: 3, step: 530000, train_cor_macbert_loss = 0.13913630715942915 Global epoch: 3, step: 530000, train_det_loss = 0.18615122539734494 Global epoch: 3, step: 530000, train_det_macbert_loss = 0.18336572115403812 Global epoch: 3, step: 530000, train_loss = 0.033683283912343494 Global epoch: 3, step: 540000, cor_acc = 0.7749818955165049 Global epoch: 3, step: 540000, cor_f1 = 0.7553892197754467 Global epoch: 3, step: 540000, cor_precision = 0.7764797984122518 Global epoch: 3, step: 540000, cor_recall = 0.7354140599657074 Global epoch: 3, step: 540000, det_acc = 0.8500673761790831 Global epoch: 3, step: 540000, det_f1 = 0.8528622513640394 Global epoch: 3, step: 540000, det_precision = 0.8766742914459762 Global epoch: 3, step: 540000, det_recall = 0.8303095602205848 Global epoch: 3, step: 540000, eval_cor_loss = 0.008551893259957644 Global epoch: 3, step: 540000, eval_cor_macbert_loss = 0.020898262469949296 Global epoch: 3, step: 540000, eval_det_loss = 0.09623607602795001 Global epoch: 3, step: 540000, eval_det_macbert_loss = 0.09506040991960261 Global epoch: 3, step: 540000, eval_loss = 0.026863553539154397 Global epoch: 3, step: 540000, global_step = 540000 Global epoch: 3, step: 540000, lr = 1.5464213289706636e-05 Global epoch: 3, step: 540000, train_cor_loss = 0.03951608043138441 Global epoch: 3, step: 540000, train_cor_macbert_loss = 0.048825202867632034 Global epoch: 3, step: 540000, train_det_loss = 0.06547242684016061 Global epoch: 3, step: 540000, train_det_macbert_loss = 0.06449429902462933 Global epoch: 3, step: 540000, train_loss = 0.011823137825413613 Global epoch: 3, step: 550000, cor_acc = 0.7752569003290891 Global epoch: 3, step: 550000, cor_f1 = 0.7562565996313154 Global epoch: 3, step: 550000, cor_precision = 0.7795515761250569 Global epoch: 3, step: 550000, cor_recall = 0.7343134528940173 Global epoch: 3, step: 550000, det_acc = 0.8492606953955028 Global epoch: 3, step: 550000, det_f1 = 0.8525798965535757 Global epoch: 3, step: 550000, det_precision = 0.8788419201298782 Global epoch: 3, step: 550000, det_recall = 0.8278418833124798 Global epoch: 3, step: 550000, eval_cor_loss = 0.008516791876918374 Global epoch: 3, step: 550000, eval_cor_macbert_loss = 0.020854322489310625 Global epoch: 3, step: 550000, eval_det_loss = 0.09622290992371604 Global epoch: 3, step: 550000, eval_det_macbert_loss = 0.09505676896000356 Global epoch: 3, step: 550000, eval_loss = 0.02682870038659717 Global epoch: 3, step: 550000, global_step = 550000 Global epoch: 3, step: 550000, lr = 1.5036451575195756e-05 Global epoch: 3, step: 550000, train_cor_loss = 0.07625545189641221 Global epoch: 3, step: 550000, train_cor_macbert_loss = 0.09432960952716482 Global epoch: 3, step: 550000, train_det_loss = 0.12715948952470807 Global epoch: 3, step: 550000, train_det_macbert_loss = 0.12526334467497854 Global epoch: 3, step: 550000, train_loss = 0.022857591611255428 Global epoch: 3, step: 560000, cor_acc = 0.7770169311296281 Global epoch: 3, step: 560000, cor_f1 = 0.7578037191434196 Global epoch: 3, step: 560000, cor_precision = 0.7785217678180862 Global epoch: 3, step: 560000, cor_recall = 0.7381597849761342 Global epoch: 3, step: 560000, det_acc = 0.8510665603314724 Global epoch: 3, step: 560000, det_f1 = 0.8538805996776822 Global epoch: 3, step: 560000, det_precision = 0.8772253515963881 Global epoch: 3, step: 560000, det_recall = 0.8317461420825802 Global epoch: 3, step: 560000, eval_cor_loss = 0.008477862189139306 Global epoch: 3, step: 560000, eval_cor_macbert_loss = 0.020816733199492538 Global epoch: 3, step: 560000, eval_det_loss = 0.09622816238645164 Global epoch: 3, step: 560000, eval_det_macbert_loss = 0.09505639305189187 Global epoch: 3, step: 560000, eval_loss = 0.026796545614921185 Global epoch: 3, step: 560000, global_step = 560000 Global epoch: 3, step: 560000, lr = 1.4608660208369832e-05 Global epoch: 3, step: 560000, train_cor_loss = 1.348149405531108 Global epoch: 3, step: 560000, train_cor_macbert_loss = 1.668886109368027 Global epoch: 3, step: 560000, train_det_loss = 2.2514816923265615 Global epoch: 3, step: 560000, train_det_macbert_loss = 2.217763990802108 Global epoch: 3, step: 560000, train_loss = 0.40435839240391885 Global epoch: 3, step: 570000, cor_acc = 0.7777502772965194 Global epoch: 3, step: 570000, cor_f1 = 0.7585669874519267 Global epoch: 3, step: 570000, cor_precision = 0.7789347754434367 Global epoch: 3, step: 570000, cor_recall = 0.7392372213726308 Global epoch: 3, step: 570000, det_acc = 0.8515340685128656 Global epoch: 3, step: 570000, det_f1 = 0.8542557048854863 Global epoch: 3, step: 570000, det_precision = 0.8771927682898544 Global epoch: 3, step: 570000, det_recall = 0.8324876036887715 Global epoch: 3, step: 570000, eval_cor_loss = 0.008505279245140027 Global epoch: 3, step: 570000, eval_cor_macbert_loss = 0.020867408929287304 Global epoch: 3, step: 570000, eval_det_loss = 0.09622416834665581 Global epoch: 3, step: 570000, eval_det_macbert_loss = 0.09505352378109969 Global epoch: 3, step: 570000, eval_loss = 0.02682922031087143 Global epoch: 3, step: 570000, global_step = 570000 Global epoch: 3, step: 570000, lr = 1.4181187185284314e-05 Global epoch: 3, step: 570000, train_cor_loss = 0.05773465709109943 Global epoch: 3, step: 570000, train_cor_macbert_loss = 0.07149186916397794 Global epoch: 3, step: 570000, train_det_loss = 0.0966109438670922 Global epoch: 3, step: 570000, train_det_macbert_loss = 0.09516103639679664 Global epoch: 3, step: 570000, train_loss = 0.017326043582994295 Global epoch: 3, step: 580000, cor_acc = 0.7779519474924145 Global epoch: 3, step: 580000, cor_f1 = 0.7589411232099882 Global epoch: 3, step: 580000, cor_precision = 0.7810691515448749 Global epoch: 3, step: 580000, cor_recall = 0.7380323462625701 Global epoch: 3, step: 580000, det_acc = 0.8515799026482963 Global epoch: 3, step: 580000, det_f1 = 0.8546307989230146 Global epoch: 3, step: 580000, det_precision = 0.8795487984306032 Global epoch: 3, step: 580000, det_recall = 0.8310857778395663 Global epoch: 3, step: 580000, eval_cor_loss = 0.00844870694950922 Global epoch: 3, step: 580000, eval_cor_macbert_loss = 0.02078391281422091 Global epoch: 3, step: 580000, eval_det_loss = 0.09622262424822953 Global epoch: 3, step: 580000, eval_det_macbert_loss = 0.09505122750604372 Global epoch: 3, step: 580000, eval_loss = 0.026769403208782162 Global epoch: 3, step: 580000, global_step = 580000 Global epoch: 3, step: 580000, lr = 1.3754380243031132e-05 Global epoch: 3, step: 580000, train_cor_loss = 0.20281403315261506 Global epoch: 3, step: 580000, train_cor_macbert_loss = 0.2513053016458836 Global epoch: 3, step: 580000, train_det_loss = 0.3405842853468488 Global epoch: 3, step: 580000, train_det_macbert_loss = 0.3354744612165093 Global epoch: 3, step: 580000, train_loss = 0.06092628268088266 Global epoch: 3, step: 590000, cor_acc = 0.7795103080970583 Global epoch: 3, step: 590000, cor_f1 = 0.7602387860914237 Global epoch: 3, step: 590000, cor_precision = 0.7808911906972199 Global epoch: 3, step: 590000, cor_recall = 0.7406506325594328 Global epoch: 3, step: 590000, det_acc = 0.8531107627716819 Global epoch: 3, step: 590000, det_f1 = 0.8557175474480331 Global epoch: 3, step: 590000, det_precision = 0.8789636976596472 Global epoch: 3, step: 590000, det_recall = 0.8336693081236387 Global epoch: 3, step: 590000, eval_cor_loss = 0.008392712206505719 Global epoch: 3, step: 590000, eval_cor_macbert_loss = 0.020672399063035737 Global epoch: 3, step: 590000, eval_det_loss = 0.09622157958334263 Global epoch: 3, step: 590000, eval_det_macbert_loss = 0.095047964328669 Global epoch: 3, step: 590000, eval_loss = 0.026697888980750394 Global epoch: 3, step: 590000, global_step = 590000 Global epoch: 3, step: 590000, lr = 1.3328586576864484e-05 Global epoch: 3, step: 590000, train_cor_loss = 0.04624642121804812 Global epoch: 3, step: 590000, train_cor_macbert_loss = 0.057355009641884634 Global epoch: 3, step: 590000, train_det_loss = 0.0778195313568109 Global epoch: 3, step: 590000, train_det_macbert_loss = 0.07665218140721665 Global epoch: 3, step: 590000, train_loss = 0.013903997069805683 Global epoch: 3, step: 600000, cor_acc = 0.7799503157971931 Global epoch: 3, step: 600000, cor_f1 = 0.7609796694804424 Global epoch: 3, step: 600000, cor_precision = 0.7814758741941785 Global epoch: 3, step: 600000, cor_recall = 0.7415311182167849 Global epoch: 3, step: 600000, det_acc = 0.8535966046072473 Global epoch: 3, step: 600000, det_f1 = 0.8564974438235643 Global epoch: 3, step: 600000, det_precision = 0.8795663215471772 Global epoch: 3, step: 600000, det_recall = 0.8346077204689745 Global epoch: 3, step: 600000, eval_cor_loss = 0.008346255481253645 Global epoch: 3, step: 600000, eval_cor_macbert_loss = 0.02067342930839527 Global epoch: 3, step: 600000, eval_det_loss = 0.0962176275538126 Global epoch: 3, step: 600000, eval_det_macbert_loss = 0.09504842480556666 Global epoch: 3, step: 600000, eval_loss = 0.026678320864115562 Global epoch: 3, step: 600000, global_step = 600000 Global epoch: 3, step: 600000, lr = 1.2904152557767397e-05 Global epoch: 3, step: 600000, train_cor_loss = 0.1088844502880883 Global epoch: 3, step: 600000, train_cor_macbert_loss = 0.13516271320098644 Global epoch: 3, step: 600000, train_det_loss = 0.1842052656125492 Global epoch: 3, step: 600000, train_det_macbert_loss = 0.18144499538984538 Global epoch: 3, step: 600000, train_loss = 0.03278595452166005 Global epoch: 3, step: 610000, cor_acc = 0.7807753302349458 Global epoch: 3, step: 610000, cor_f1 = 0.7625040892193309 Global epoch: 3, step: 610000, cor_precision = 0.7835079270006967 Global epoch: 3, step: 610000, cor_recall = 0.7425969692756847 Global epoch: 3, step: 610000, det_acc = 0.8529640935383036 Global epoch: 3, step: 610000, det_f1 = 0.8561843866171004 Global epoch: 3, step: 610000, det_precision = 0.8797687296018776 Global epoch: 3, step: 610000, det_recall = 0.8338315028499931 Global epoch: 3, step: 610000, eval_cor_loss = 0.008336647123784579 Global epoch: 3, step: 610000, eval_cor_macbert_loss = 0.020613978865901262 Global epoch: 3, step: 610000, eval_det_loss = 0.09621747259003646 Global epoch: 3, step: 610000, eval_det_macbert_loss = 0.09504869131617656 Global epoch: 3, step: 610000, eval_loss = 0.026648979253435685 Global epoch: 3, step: 610000, global_step = 610000 Global epoch: 3, step: 610000, lr = 1.2481423450688884e-05 Global epoch: 3, step: 610000, train_cor_loss = 0.038432173381046826 Global epoch: 3, step: 610000, train_cor_macbert_loss = 0.047734447322179026 Global epoch: 3, step: 610000, train_det_loss = 0.06519543837470386 Global epoch: 3, step: 610000, train_det_macbert_loss = 0.06421761749118726 Global epoch: 3, step: 610000, train_loss = 0.011581698603924682 Global epoch: 3, step: 620000, cor_acc = 0.781316173033028 Global epoch: 3, step: 620000, cor_f1 = 0.7622696653241615 Global epoch: 3, step: 620000, cor_precision = 0.78220320386219 Global epoch: 3, step: 620000, cor_recall = 0.7433268455442792 Global epoch: 3, step: 620000, det_acc = 0.8540732796157267 Global epoch: 3, step: 620000, det_f1 = 0.8565658005726438 Global epoch: 3, step: 620000, det_precision = 0.8789652061541462 Global epoch: 3, step: 620000, det_recall = 0.8352796700495853 Global epoch: 3, step: 620000, eval_cor_loss = 0.008300327631764255 Global epoch: 3, step: 620000, eval_cor_macbert_loss = 0.02058774913076614 Global epoch: 3, step: 620000, eval_det_loss = 0.09621152644570151 Global epoch: 3, step: 620000, eval_det_macbert_loss = 0.09503973677985936 Global epoch: 3, step: 620000, eval_loss = 0.026621278264534958 Global epoch: 3, step: 620000, global_step = 620000 Global epoch: 3, step: 620000, lr = 1.2060743133680712e-05 Global epoch: 3, step: 620000, train_cor_loss = 0.07452964922028422 Global epoch: 3, step: 620000, train_cor_macbert_loss = 0.09257315809659947 Global epoch: 3, step: 620000, train_det_loss = 0.12622862770323875 Global epoch: 3, step: 620000, train_det_macbert_loss = 0.12432816498445863 Global epoch: 3, step: 620000, train_loss = 0.02245261382458694 Global epoch: 4, step: 630000, cor_acc = 0.7814536754393202 Global epoch: 4, step: 630000, cor_f1 = 0.7627833985234149 Global epoch: 4, step: 630000, cor_precision = 0.7832987425222806 Global epoch: 4, step: 630000, cor_recall = 0.7433152602066824 Global epoch: 4, step: 630000, det_acc = 0.853770774321884 Global epoch: 4, step: 630000, det_f1 = 0.8565738946417321 Global epoch: 4, step: 630000, det_precision = 0.8796117690147723 Global epoch: 4, step: 630000, det_recall = 0.8347119885073451 Global epoch: 4, step: 630000, eval_cor_loss = 0.00829097492104927 Global epoch: 4, step: 630000, eval_cor_macbert_loss = 0.020610812056795467 Global epoch: 4, step: 630000, eval_det_loss = 0.0962075665855261 Global epoch: 4, step: 630000, eval_det_macbert_loss = 0.09504155484166044 Global epoch: 4, step: 630000, eval_loss = 0.026626944467665618 Global epoch: 4, step: 630000, global_step = 630000 Global epoch: 4, step: 630000, lr = 1.1642453818162484e-05 Global epoch: 4, step: 630000, train_cor_loss = 0.05914569197028911 Global epoch: 4, step: 630000, train_cor_macbert_loss = 0.07359031912416131 Global epoch: 4, step: 630000, train_det_loss = 0.1008477624550107 Global epoch: 4, step: 630000, train_det_macbert_loss = 0.09931413130465126 Global epoch: 4, step: 630000, train_loss = 0.017856237238332157 Global epoch: 4, step: 640000, cor_acc = 0.782810365848069 Global epoch: 4, step: 640000, cor_f1 = 0.7642612664004564 Global epoch: 4, step: 640000, cor_precision = 0.7845117845117845 Global epoch: 4, step: 640000, cor_recall = 0.7450298901709996 Global epoch: 4, step: 640000, det_acc = 0.8544032853908277 Global epoch: 4, step: 640000, det_f1 = 0.8570783418900931 Global epoch: 4, step: 640000, det_precision = 0.8797882203679305 Global epoch: 4, step: 640000, det_recall = 0.83551137680152 Global epoch: 4, step: 640000, eval_cor_loss = 0.008257770369532982 Global epoch: 4, step: 640000, eval_cor_macbert_loss = 0.02056703163456686 Global epoch: 4, step: 640000, eval_det_loss = 0.09619218607306725 Global epoch: 4, step: 640000, eval_det_macbert_loss = 0.0950446145249161 Global epoch: 4, step: 640000, eval_loss = 0.02659330182094198 Global epoch: 4, step: 640000, global_step = 640000 Global epoch: 4, step: 640000, lr = 1.1226895770542356e-05 Global epoch: 4, step: 640000, train_cor_loss = 0.05625683363435886 Global epoch: 4, step: 640000, train_cor_macbert_loss = 0.06997352191762814 Global epoch: 4, step: 640000, train_det_loss = 0.09603604438698912 Global epoch: 4, step: 640000, train_det_macbert_loss = 0.09458511557164428 Global epoch: 4, step: 640000, train_loss = 0.016986122547104233 Global epoch: 4, step: 650000, cor_acc = 0.7828928672918443 Global epoch: 4, step: 650000, cor_f1 = 0.7644547508621715 Global epoch: 4, step: 650000, cor_precision = 0.7852413759405844 Global epoch: 4, step: 650000, cor_recall = 0.7447402567310811 Global epoch: 4, step: 650000, det_acc = 0.8547607916471872 Global epoch: 4, step: 650000, det_f1 = 0.8576881912236889 Global epoch: 4, step: 650000, det_precision = 0.8810099677513925 Global epoch: 4, step: 650000, det_recall = 0.8355693034895036 Global epoch: 4, step: 650000, eval_cor_loss = 0.008262192013624884 Global epoch: 4, step: 650000, eval_cor_macbert_loss = 0.020566341108433646 Global epoch: 4, step: 650000, eval_det_loss = 0.09619788722632323 Global epoch: 4, step: 650000, eval_det_macbert_loss = 0.09504864231621335 Global epoch: 4, step: 650000, eval_loss = 0.026595617190431513 Global epoch: 4, step: 650000, global_step = 650000 Global epoch: 4, step: 650000, lr = 1.0814407035420124e-05 Global epoch: 4, step: 650000, train_cor_loss = 0.19460992413708084 Global epoch: 4, step: 650000, train_cor_macbert_loss = 0.24233372841120895 Global epoch: 4, step: 650000, train_det_loss = 0.33406755507325847 Global epoch: 4, step: 650000, train_det_macbert_loss = 0.32903421695892493 Global epoch: 4, step: 650000, train_loss = 0.05885842312196834 Global epoch: 4, step: 660000, cor_acc = 0.7844695615506605 Global epoch: 4, step: 660000, cor_f1 = 0.7666311535416902 Global epoch: 4, step: 660000, cor_precision = 0.7883031200656083 Global epoch: 4, step: 660000, cor_recall = 0.7461189119050929 Global epoch: 4, step: 660000, det_acc = 0.8542566161574494 Global epoch: 4, step: 660000, det_f1 = 0.8572550933558714 Global epoch: 4, step: 660000, det_precision = 0.8814889163616779 Global epoch: 4, step: 660000, det_recall = 0.8343180870290561 Global epoch: 4, step: 660000, eval_cor_loss = 0.008141431869199113 Global epoch: 4, step: 660000, eval_cor_macbert_loss = 0.020432644082182524 Global epoch: 4, step: 660000, eval_det_loss = 0.09619225775896717 Global epoch: 4, step: 660000, eval_det_macbert_loss = 0.09503700612131992 Global epoch: 4, step: 660000, eval_loss = 0.02648617797652688 Global epoch: 4, step: 660000, global_step = 660000 Global epoch: 4, step: 660000, lr = 1.0405323160597528e-05 Global epoch: 4, step: 660000, train_cor_loss = 0.04540836078136808 Global epoch: 4, step: 660000, train_cor_macbert_loss = 0.05649003123736832 Global epoch: 4, step: 660000, train_det_loss = 0.07747342170574857 Global epoch: 4, step: 660000, train_det_macbert_loss = 0.07630353667232233 Global epoch: 4, step: 660000, train_loss = 0.0137100225435653 Global epoch: 4, step: 670000, cor_acc = 0.783791216346286 Global epoch: 4, step: 670000, cor_f1 = 0.7649988424757959 Global epoch: 4, step: 670000, cor_precision = 0.7844108731907434 Global epoch: 4, step: 670000, cor_recall = 0.7465243987209788 Global epoch: 4, step: 670000, det_acc = 0.8558333104162656 Global epoch: 4, step: 670000, det_f1 = 0.8583012293500651 Global epoch: 4, step: 670000, det_precision = 0.8800808307059296 Global epoch: 4, step: 670000, det_recall = 0.8375735668937393 Global epoch: 4, step: 670000, eval_cor_loss = 0.008158524816835856 Global epoch: 4, step: 670000, eval_cor_macbert_loss = 0.020469332479182943 Global epoch: 4, step: 670000, eval_det_loss = 0.09620321697326951 Global epoch: 4, step: 670000, eval_det_macbert_loss = 0.09503622950259208 Global epoch: 4, step: 670000, eval_loss = 0.026509798739386144 Global epoch: 4, step: 670000, global_step = 670000 Global epoch: 4, step: 670000, lr = 9.999976924119725e-06 Global epoch: 4, step: 670000, train_cor_loss = 0.10577120115889624 Global epoch: 4, step: 670000, train_cor_macbert_loss = 0.13182907645026198 Global epoch: 4, step: 670000, train_det_loss = 0.1823193464071421 Global epoch: 4, step: 670000, train_det_macbert_loss = 0.17955824532587533 Global epoch: 4, step: 670000, train_loss = 0.03203023533363893 Global epoch: 4, step: 680000, cor_acc = 0.7846803985736417 Global epoch: 4, step: 680000, cor_f1 = 0.7666188966919788 Global epoch: 4, step: 680000, cor_precision = 0.7875285579895175 Global epoch: 4, step: 680000, cor_recall = 0.7467908614857037 Global epoch: 4, step: 680000, det_acc = 0.85651165562064 Global epoch: 4, step: 680000, det_f1 = 0.8598119726224527 Global epoch: 4, step: 680000, det_precision = 0.8832634909775079 Global epoch: 4, step: 680000, det_recall = 0.8375735668937393 Global epoch: 4, step: 680000, eval_cor_loss = 0.008130522208302031 Global epoch: 4, step: 680000, eval_cor_macbert_loss = 0.020398529959890072 Global epoch: 4, step: 680000, eval_det_loss = 0.09618526205695714 Global epoch: 4, step: 680000, eval_det_macbert_loss = 0.09503693728153742 Global epoch: 4, step: 680000, eval_loss = 0.026466513036746707 Global epoch: 4, step: 680000, global_step = 680000 Global epoch: 4, step: 680000, lr = 9.598698063569871e-06 Global epoch: 4, step: 680000, train_cor_loss = 0.03787847014780553 Global epoch: 4, step: 680000, train_cor_macbert_loss = 0.047172953353337606 Global epoch: 4, step: 680000, train_det_loss = 0.06492025289100331 Global epoch: 4, step: 680000, train_det_macbert_loss = 0.06393599175844125 Global epoch: 4, step: 680000, train_loss = 0.011452768684791696 Global epoch: 4, step: 690000, cor_acc = 0.7847537331903308 Global epoch: 4, step: 690000, cor_f1 = 0.7664101268831902 Global epoch: 4, step: 690000, cor_precision = 0.7868308338112728 Global epoch: 4, step: 690000, cor_recall = 0.7470225682376385 Global epoch: 4, step: 690000, det_acc = 0.8559708128225577 Global epoch: 4, step: 690000, det_f1 = 0.8587525629215821 Global epoch: 4, step: 690000, det_precision = 0.8816336990079195 Global epoch: 4, step: 690000, det_recall = 0.8370290560266926 Global epoch: 4, step: 690000, eval_cor_loss = 0.00813540618936852 Global epoch: 4, step: 690000, eval_cor_macbert_loss = 0.02043698447459134 Global epoch: 4, step: 690000, eval_det_loss = 0.09618881273150828 Global epoch: 4, step: 690000, eval_det_macbert_loss = 0.09503686019391197 Global epoch: 4, step: 690000, eval_loss = 0.026485192419907034 Global epoch: 4, step: 690000, global_step = 690000 Global epoch: 4, step: 690000, lr = 9.201813007836999e-06 Global epoch: 4, step: 690000, train_cor_loss = 0.07241262401471779 Global epoch: 4, step: 690000, train_cor_macbert_loss = 0.09035768374313194 Global epoch: 4, step: 690000, train_det_loss = 0.1253857589272036 Global epoch: 4, step: 690000, train_det_macbert_loss = 0.12349046891572119 Global epoch: 4, step: 690000, train_loss = 0.021960775150370825 Global epoch: 4, step: 700000, cor_acc = 0.7846070639569526 Global epoch: 4, step: 700000, cor_f1 = 0.7662733676107827 Global epoch: 4, step: 700000, cor_precision = 0.7868382182399688 Global epoch: 4, step: 700000, cor_recall = 0.7467561054729135 Global epoch: 4, step: 700000, det_acc = 0.8563283190789173 Global epoch: 4, step: 700000, det_f1 = 0.8592861176330728 Global epoch: 4, step: 700000, det_precision = 0.8823471966210525 Global epoch: 4, step: 700000, det_recall = 0.8373997868297882 Global epoch: 4, step: 700000, eval_cor_loss = 0.008146898087043926 Global epoch: 4, step: 700000, eval_cor_macbert_loss = 0.02042544682050679 Global epoch: 4, step: 700000, eval_det_loss = 0.09619355397214291 Global epoch: 4, step: 700000, eval_det_macbert_loss = 0.09503797891245878 Global epoch: 4, step: 700000, eval_loss = 0.026485612435193748 Global epoch: 4, step: 700000, global_step = 700000 Global epoch: 4, step: 700000, lr = 8.809644611575447e-06 Global epoch: 4, step: 700000, train_cor_loss = 1.0385542284244325 Global epoch: 4, step: 700000, train_cor_macbert_loss = 1.2964267650486747 Global epoch: 4, step: 700000, train_det_loss = 1.8015592281895783 Global epoch: 4, step: 700000, train_det_macbert_loss = 1.774365431287085 Global epoch: 4, step: 700000, train_loss = 0.3151403277188433 Global epoch: 4, step: 710000, cor_acc = 0.7855879144551696 Global epoch: 4, step: 710000, cor_f1 = 0.7678164747016465 Global epoch: 4, step: 710000, cor_precision = 0.7887291251817193 Global epoch: 4, step: 710000, cor_recall = 0.7479841512581676 Global epoch: 4, step: 710000, det_acc = 0.8565208224477262 Global epoch: 4, step: 710000, det_f1 = 0.859840759218186 Global epoch: 4, step: 710000, det_precision = 0.8832598311689899 Global epoch: 4, step: 710000, det_recall = 0.837631493581723 Global epoch: 4, step: 710000, eval_cor_loss = 0.008123554770599388 Global epoch: 4, step: 710000, eval_cor_macbert_loss = 0.020391106798838605 Global epoch: 4, step: 710000, eval_det_loss = 0.09619726914267007 Global epoch: 4, step: 710000, eval_det_macbert_loss = 0.09503443052703353 Global epoch: 4, step: 710000, eval_loss = 0.026461109543577978 Global epoch: 4, step: 710000, global_step = 710000 Global epoch: 4, step: 710000, lr = 8.42251189257182e-06 Global epoch: 4, step: 710000, train_cor_loss = 0.055051417398680975 Global epoch: 4, step: 710000, train_cor_macbert_loss = 0.06873668026317507 Global epoch: 4, step: 710000, train_det_loss = 0.09553264174759689 Global epoch: 4, step: 710000, train_det_macbert_loss = 0.09408888473458199 Global epoch: 4, step: 710000, train_loss = 0.016707889511208968 Global epoch: 4, step: 720000, cor_acc = 0.7866696000513342 Global epoch: 4, step: 720000, cor_f1 = 0.7690944764849278 Global epoch: 4, step: 720000, cor_precision = 0.7899577399418619 Global epoch: 4, step: 720000, cor_recall = 0.7493048797441958 Global epoch: 4, step: 720000, det_acc = 0.8566216575456738 Global epoch: 4, step: 720000, det_f1 = 0.8598370890064807 Global epoch: 4, step: 720000, det_precision = 0.8831619317487848 Global epoch: 4, step: 720000, det_recall = 0.8377125909449001 Global epoch: 4, step: 720000, eval_cor_loss = 0.008073868564410518 Global epoch: 4, step: 720000, eval_cor_macbert_loss = 0.020358621755495288 Global epoch: 4, step: 720000, eval_det_loss = 0.09618428930295105 Global epoch: 4, step: 720000, eval_det_macbert_loss = 0.09503414747486782 Global epoch: 4, step: 720000, eval_loss = 0.026425192040852422 Global epoch: 4, step: 720000, global_step = 720000 Global epoch: 4, step: 720000, lr = 8.040729772233142e-06 Global epoch: 4, step: 720000, train_cor_loss = 0.1888074845106922 Global epoch: 4, step: 720000, train_cor_macbert_loss = 0.23581975470968425 Global epoch: 4, step: 720000, train_det_loss = 0.3279870527384564 Global epoch: 4, step: 720000, train_det_macbert_loss = 0.3230109342467459 Global epoch: 4, step: 720000, train_loss = 0.05732285819148938 Global epoch: 4, step: 730000, cor_acc = 0.7866329327429896 Global epoch: 4, step: 730000, cor_f1 = 0.7687914801666923 Global epoch: 4, step: 730000, cor_precision = 0.7883440064282062 Global epoch: 4, step: 730000, cor_recall = 0.7501853654015478 Global epoch: 4, step: 730000, det_acc = 0.8574833392917709 Global epoch: 4, step: 730000, det_f1 = 0.860555403849122 Global epoch: 4, step: 730000, det_precision = 0.8824417443814069 Global epoch: 4, step: 730000, det_recall = 0.8397284396867325 Global epoch: 4, step: 730000, eval_cor_loss = 0.008063555559503421 Global epoch: 4, step: 730000, eval_cor_macbert_loss = 0.020337512085393913 Global epoch: 4, step: 730000, eval_det_loss = 0.09619688485129003 Global epoch: 4, step: 730000, eval_det_macbert_loss = 0.0950283171476349 Global epoch: 4, step: 730000, eval_loss = 0.026412344778219264 Global epoch: 4, step: 730000, global_step = 730000 Global epoch: 4, step: 730000, lr = 7.664608819407279e-06 Global epoch: 4, step: 730000, train_cor_loss = 0.04419792597691918 Global epoch: 4, step: 730000, train_cor_macbert_loss = 0.05525037494997455 Global epoch: 4, step: 730000, train_det_loss = 0.07714819836979073 Global epoch: 4, step: 730000, train_det_macbert_loss = 0.07597795146584185 Global epoch: 4, step: 730000, train_loss = 0.013437497697068281 Global epoch: 4, step: 740000, cor_acc = 0.7868712702472294 Global epoch: 4, step: 740000, cor_f1 = 0.7696322008511447 Global epoch: 4, step: 740000, cor_precision = 0.7902426520847573 Global epoch: 4, step: 740000, cor_recall = 0.7500695120255805 Global epoch: 4, step: 740000, det_acc = 0.8568049940873965 Global epoch: 4, step: 740000, det_f1 = 0.8603219134114738 Global epoch: 4, step: 740000, det_precision = 0.8833609999023533 Global epoch: 4, step: 740000, det_recall = 0.8384540525510913 Global epoch: 4, step: 740000, eval_cor_loss = 0.008023214764014974 Global epoch: 4, step: 740000, eval_cor_macbert_loss = 0.020294672443947285 Global epoch: 4, step: 740000, eval_det_loss = 0.09617706406583047 Global epoch: 4, step: 740000, eval_det_macbert_loss = 0.09503217078188374 Global epoch: 4, step: 740000, eval_loss = 0.026375795555923804 Global epoch: 4, step: 740000, global_step = 740000 Global epoch: 4, step: 740000, lr = 7.294454997744061e-06 Global epoch: 4, step: 740000, train_cor_loss = 0.10319552695040932 Global epoch: 4, step: 740000, train_cor_macbert_loss = 0.1290652230096292 Global epoch: 4, step: 740000, train_det_loss = 0.1804844008541015 Global epoch: 4, step: 740000, train_det_macbert_loss = 0.1777456233393995 Global epoch: 4, step: 740000, train_loss = 0.0313945186117498 Global epoch: 4, step: 750000, cor_acc = 0.7888879722061802 Global epoch: 4, step: 750000, cor_f1 = 0.7715037946999008 Global epoch: 4, step: 750000, cor_precision = 0.7920800536945513 Global epoch: 4, step: 750000, cor_recall = 0.7519695073914454 Global epoch: 4, step: 750000, det_acc = 0.8591700354756209 Global epoch: 4, step: 750000, det_f1 = 0.862636023796364 Global epoch: 4, step: 750000, det_precision = 0.8856428092012936 Global epoch: 4, step: 750000, det_recall = 0.8407942907456323 Global epoch: 4, step: 750000, eval_cor_loss = 0.008010643525411885 Global epoch: 4, step: 750000, eval_cor_macbert_loss = 0.020280220148289303 Global epoch: 4, step: 750000, eval_det_loss = 0.09618125858980692 Global epoch: 4, step: 750000, eval_det_macbert_loss = 0.09502914781638234 Global epoch: 4, step: 750000, eval_loss = 0.02636439843380147 Global epoch: 4, step: 750000, global_step = 750000 Global epoch: 4, step: 750000, lr = 6.930569416802588e-06 Global epoch: 4, step: 750000, train_cor_loss = 0.03705685820640912 Global epoch: 4, step: 750000, train_cor_macbert_loss = 0.04633021599743391 Global epoch: 4, step: 750000, train_det_loss = 0.0646763262395363 Global epoch: 4, step: 750000, train_det_macbert_loss = 0.06369575463477788 Global epoch: 4, step: 750000, train_loss = 0.011266853501676964 Global epoch: 4, step: 760000, cor_acc = 0.7879896231517385 Global epoch: 4, step: 760000, cor_f1 = 0.7702890379250994 Global epoch: 4, step: 760000, cor_precision = 0.7897023389393238 Global epoch: 4, step: 760000, cor_recall = 0.751807312665091 Global epoch: 4, step: 760000, det_acc = 0.8582166854586621 Global epoch: 4, step: 760000, det_f1 = 0.8612261855302985 Global epoch: 4, step: 760000, det_precision = 0.882931340813396 Global epoch: 4, step: 760000, det_recall = 0.8405625839936975 Global epoch: 4, step: 760000, eval_cor_loss = 0.007951817893318636 Global epoch: 4, step: 760000, eval_cor_macbert_loss = 0.020229300164337192 Global epoch: 4, step: 760000, eval_det_loss = 0.09618471017447569 Global epoch: 4, step: 760000, eval_det_macbert_loss = 0.0950239915755689 Global epoch: 4, step: 760000, eval_loss = 0.026317628706652236 Global epoch: 4, step: 760000, global_step = 760000 Global epoch: 4, step: 760000, lr = 6.573248087107208e-06 Global epoch: 4, step: 760000, train_cor_loss = 0.07090002516146482 Global epoch: 4, step: 760000, train_cor_macbert_loss = 0.08875850910628229 Global epoch: 4, step: 760000, train_det_loss = 0.12447894473925539 Global epoch: 4, step: 760000, train_det_macbert_loss = 0.12258831010108821 Global epoch: 4, step: 760000, train_loss = 0.021596230961363354 Global epoch: 4, step: 770000, cor_acc = 0.7884296308518732 Global epoch: 4, step: 770000, cor_f1 = 0.7708880152970937 Global epoch: 4, step: 770000, cor_precision = 0.7907702054043517 Global epoch: 4, step: 770000, cor_recall = 0.7519810927290421 Global epoch: 4, step: 770000, det_acc = 0.858592525369194 Global epoch: 4, step: 770000, det_f1 = 0.8617917077399968 Global epoch: 4, step: 770000, det_precision = 0.8840184206037864 Global epoch: 4, step: 770000, det_recall = 0.8406552666944714 Global epoch: 4, step: 770000, eval_cor_loss = 0.00798739999532802 Global epoch: 4, step: 770000, eval_cor_macbert_loss = 0.02025963286933391 Global epoch: 4, step: 770000, eval_det_loss = 0.09618353124186986 Global epoch: 4, step: 770000, eval_det_macbert_loss = 0.09502601196071474 Global epoch: 4, step: 770000, eval_loss = 0.026345705596019675 Global epoch: 4, step: 770000, global_step = 770000 Global epoch: 4, step: 770000, lr = 6.222781679351415e-06 Global epoch: 4, step: 770000, train_cor_loss = 0.9308346408142686 Global epoch: 4, step: 770000, train_cor_macbert_loss = 1.1655036447342428 Global epoch: 4, step: 770000, train_det_loss = 1.637105852157297 Global epoch: 4, step: 770000, train_det_macbert_loss = 1.612298667057324 Global epoch: 4, step: 770000, train_loss = 0.2836622863203716 Global epoch: 4, step: 780000, cor_acc = 0.7891996443271091 Global epoch: 4, step: 780000, cor_f1 = 0.7718340287381223 Global epoch: 4, step: 780000, cor_precision = 0.7913010672865123 Global epoch: 4, step: 780000, cor_recall = 0.7533018212150702 Global epoch: 4, step: 780000, det_acc = 0.8594817075965496 Global epoch: 4, step: 780000, det_f1 = 0.8628440176393432 Global epoch: 4, step: 780000, det_precision = 0.8846064913412275 Global epoch: 4, step: 780000, det_recall = 0.8421266045692571 Global epoch: 4, step: 780000, eval_cor_loss = 0.007901082757059884 Global epoch: 4, step: 780000, eval_cor_macbert_loss = 0.020149336961253372 Global epoch: 4, step: 780000, eval_det_loss = 0.09618029858981435 Global epoch: 4, step: 780000, eval_det_macbert_loss = 0.09502101432487295 Global epoch: 4, step: 780000, eval_loss = 0.026261527734535314 Global epoch: 4, step: 780000, global_step = 780000 Global epoch: 4, step: 780000, lr = 5.87945528794554e-06 Global epoch: 4, step: 780000, train_cor_loss = 0.054207046759033095 Global epoch: 4, step: 780000, train_cor_macbert_loss = 0.0678394946505806 Global epoch: 4, step: 780000, train_det_loss = 0.09499853757997735 Global epoch: 4, step: 780000, train_det_macbert_loss = 0.0935517153120073 Global epoch: 4, step: 780000, train_loss = 0.01650276277437587 Global epoch: 5, step: 790000, cor_acc = 0.7905288342545994 Global epoch: 5, step: 790000, cor_f1 = 0.7734092300013665 Global epoch: 5, step: 790000, cor_precision = 0.7938475049705427 Global epoch: 5, step: 790000, cor_recall = 0.7539969414708745 Global epoch: 5, step: 790000, det_acc = 0.8597567124091339 Global epoch: 5, step: 790000, det_f1 = 0.8631542671079447 Global epoch: 5, step: 790000, det_precision = 0.885964163302148 Global epoch: 5, step: 790000, det_recall = 0.8414894110014366 Global epoch: 5, step: 790000, eval_cor_loss = 0.007901094535638599 Global epoch: 5, step: 790000, eval_cor_macbert_loss = 0.020153455559914588 Global epoch: 5, step: 790000, eval_det_loss = 0.09618016377384102 Global epoch: 5, step: 790000, eval_det_macbert_loss = 0.09502186767081996 Global epoch: 5, step: 790000, eval_loss = 0.026263337051023558 Global epoch: 5, step: 790000, global_step = 790000 Global epoch: 5, step: 790000, lr = 5.543548199100593e-06 Global epoch: 5, step: 790000, train_cor_loss = 0.057782647225299306 Global epoch: 5, step: 790000, train_cor_macbert_loss = 0.0722596003609998 Global epoch: 5, step: 790000, train_det_loss = 0.10085645295655765 Global epoch: 5, step: 790000, train_det_macbert_loss = 0.0993173839982611 Global epoch: 5, step: 790000, train_loss = 0.017570248794869875 Global epoch: 5, step: 800000, cor_acc = 0.7900613260732062 Global epoch: 5, step: 800000, cor_f1 = 0.7721576790553965 Global epoch: 5, step: 800000, cor_precision = 0.790972601907539 Global epoch: 5, step: 800000, cor_recall = 0.7542170628852125 Global epoch: 5, step: 800000, det_acc = 0.8609300662761599 Global epoch: 5, step: 800000, det_f1 = 0.8638544428036841 Global epoch: 5, step: 800000, det_precision = 0.8849037118036571 Global epoch: 5, step: 800000, det_recall = 0.8437833078455906 Global epoch: 5, step: 800000, eval_cor_loss = 0.00789706692306839 Global epoch: 5, step: 800000, eval_cor_macbert_loss = 0.02016802797707224 Global epoch: 5, step: 800000, eval_det_loss = 0.09617352182478613 Global epoch: 5, step: 800000, eval_det_macbert_loss = 0.09502349498596264 Global epoch: 5, step: 800000, eval_loss = 0.026267442475470304 Global epoch: 5, step: 800000, global_step = 800000 Global epoch: 5, step: 800000, lr = 5.215333663636913e-06 Global epoch: 5, step: 800000, train_cor_loss = 0.04333010808787671 Global epoch: 5, step: 800000, train_cor_macbert_loss = 0.05434307550877904 Global epoch: 5, step: 800000, train_det_loss = 0.07678561488425632 Global epoch: 5, step: 800000, train_det_macbert_loss = 0.07561545889444882 Global epoch: 5, step: 800000, train_loss = 0.013235296297122043 Global epoch: 5, step: 810000, cor_acc = 0.7910605102255956 Global epoch: 5, step: 810000, cor_f1 = 0.7733652899229957 Global epoch: 5, step: 810000, cor_precision = 0.7925005471390706 Global epoch: 5, step: 810000, cor_recall = 0.7551323045553547 Global epoch: 5, step: 810000, det_acc = 0.8610217345470212 Global epoch: 5, step: 810000, det_f1 = 0.8639195073622762 Global epoch: 5, step: 810000, det_precision = 0.8852953335116601 Global epoch: 5, step: 810000, det_recall = 0.8435516010936559 Global epoch: 5, step: 810000, eval_cor_loss = 0.007865851276634849 Global epoch: 5, step: 810000, eval_cor_macbert_loss = 0.020141828926708807 Global epoch: 5, step: 810000, eval_det_loss = 0.09617459404000227 Global epoch: 5, step: 810000, eval_det_macbert_loss = 0.09502157643852399 Global epoch: 5, step: 810000, eval_loss = 0.02624297776944527 Global epoch: 5, step: 810000, global_step = 810000 Global epoch: 5, step: 810000, lr = 4.895078674702432e-06 Global epoch: 5, step: 810000, train_cor_loss = 0.10114095047929589 Global epoch: 5, step: 810000, train_cor_macbert_loss = 0.12672836811113175 Global epoch: 5, step: 810000, train_det_loss = 0.17862026896128824 Global epoch: 5, step: 810000, train_det_macbert_loss = 0.1758986214218375 Global epoch: 5, step: 810000, train_loss = 0.030858345252358404 Global epoch: 5, step: 820000, cor_acc = 0.7902904967503598 Global epoch: 5, step: 820000, cor_f1 = 0.7729659728162722 Global epoch: 5, step: 820000, cor_precision = 0.7932089734211168 Global epoch: 5, step: 820000, cor_recall = 0.7537304787061495 Global epoch: 5, step: 820000, det_acc = 0.8597567124091339 Global epoch: 5, step: 820000, det_f1 = 0.8630001900959986 Global epoch: 5, step: 820000, det_precision = 0.8856010729090465 Global epoch: 5, step: 820000, det_recall = 0.8415241670142268 Global epoch: 5, step: 820000, eval_cor_loss = 0.007885636580254637 Global epoch: 5, step: 820000, eval_cor_macbert_loss = 0.02015337622712187 Global epoch: 5, step: 820000, eval_det_loss = 0.09617293206906605 Global epoch: 5, step: 820000, eval_det_macbert_loss = 0.09502222473732853 Global epoch: 5, step: 820000, eval_loss = 0.026256218102081574 Global epoch: 5, step: 820000, global_step = 820000 Global epoch: 5, step: 820000, lr = 4.5830437505813675e-06 Global epoch: 5, step: 820000, train_cor_loss = 0.03638433778892997 Global epoch: 5, step: 820000, train_cor_macbert_loss = 0.04562245826895223 Global epoch: 5, step: 820000, train_det_loss = 0.06444619390066642 Global epoch: 5, step: 820000, train_det_macbert_loss = 0.06346102290829018 Global epoch: 5, step: 820000, train_loss = 0.011111482737645804 Global epoch: 5, step: 830000, cor_acc = 0.7908680068567867 Global epoch: 5, step: 830000, cor_f1 = 0.7736552248017853 Global epoch: 5, step: 830000, cor_precision = 0.7930841485374994 Global epoch: 5, step: 830000, cor_recall = 0.7551554752305483 Global epoch: 5, step: 830000, det_acc = 0.8604717249218528 Global epoch: 5, step: 830000, det_f1 = 0.8637777144756208 Global epoch: 5, step: 830000, det_precision = 0.8854698982819876 Global epoch: 5, step: 830000, det_recall = 0.8431229436025766 Global epoch: 5, step: 830000, eval_cor_loss = 0.007892106686945654 Global epoch: 5, step: 830000, eval_cor_macbert_loss = 0.020171405764187984 Global epoch: 5, step: 830000, eval_det_loss = 0.09617091538627558 Global epoch: 5, step: 830000, eval_det_macbert_loss = 0.09502358773051033 Global epoch: 5, step: 830000, eval_loss = 0.026266581433757208 Global epoch: 5, step: 830000, global_step = 830000 Global epoch: 5, step: 830000, lr = 4.279482722770055e-06 Global epoch: 5, step: 830000, train_cor_loss = 0.0695194387326935 Global epoch: 5, step: 830000, train_cor_macbert_loss = 0.08724371225616495 Global epoch: 5, step: 830000, train_det_loss = 0.12358119049575605 Global epoch: 5, step: 830000, train_det_macbert_loss = 0.1216944704290992 Global epoch: 5, step: 830000, train_loss = 0.021255004091643756 Global epoch: 5, step: 840000, cor_acc = 0.7906755034879777 Global epoch: 5, step: 840000, cor_f1 = 0.7733969678621885 Global epoch: 5, step: 840000, cor_precision = 0.793027049399849 Global epoch: 5, step: 840000, cor_recall = 0.7547152324018722 Global epoch: 5, step: 840000, det_acc = 0.8605175590572836 Global epoch: 5, step: 840000, det_f1 = 0.8638506013225534 Global epoch: 5, step: 840000, det_precision = 0.8857765442017871 Global epoch: 5, step: 840000, det_recall = 0.8429839195514157 Global epoch: 5, step: 840000, eval_cor_loss = 0.007872245665018143 Global epoch: 5, step: 840000, eval_cor_macbert_loss = 0.020163906551406062 Global epoch: 5, step: 840000, eval_det_loss = 0.09617140593416214 Global epoch: 5, step: 840000, eval_det_macbert_loss = 0.09502661782550309 Global epoch: 5, step: 840000, eval_loss = 0.026255217361436215 Global epoch: 5, step: 840000, global_step = 840000 Global epoch: 5, step: 840000, lr = 3.984642529492266e-06 Global epoch: 5, step: 840000, train_cor_loss = 0.8426866873490017 Global epoch: 5, step: 840000, train_cor_macbert_loss = 1.0579087552166624 Global epoch: 5, step: 840000, train_det_loss = 1.500172901587106 Global epoch: 5, step: 840000, train_det_macbert_loss = 1.4772670215664607 Global epoch: 5, step: 840000, train_loss = 0.2577652722172908 Global epoch: 5, step: 850000, cor_acc = 0.7922338640926216 Global epoch: 5, step: 850000, cor_f1 = 0.7749715018523795 Global epoch: 5, step: 850000, cor_precision = 0.7947902966535145 Global epoch: 5, step: 850000, cor_recall = 0.7561170582510774 Global epoch: 5, step: 850000, det_acc = 0.861590077826362 Global epoch: 5, step: 850000, det_f1 = 0.8648119122257053 Global epoch: 5, step: 850000, det_precision = 0.8869282478445126 Global epoch: 5, step: 850000, det_recall = 0.8437717225079939 Global epoch: 5, step: 850000, eval_cor_loss = 0.007820921548100516 Global epoch: 5, step: 850000, eval_cor_macbert_loss = 0.020102407553920437 Global epoch: 5, step: 850000, eval_det_loss = 0.09616193074838957 Global epoch: 5, step: 850000, eval_det_macbert_loss = 0.09501942642725517 Global epoch: 5, step: 850000, eval_loss = 0.026206017536559226 Global epoch: 5, step: 850000, global_step = 850000 Global epoch: 5, step: 850000, lr = 3.698763014822026e-06 Global epoch: 5, step: 850000, train_cor_loss = 0.053016750500355654 Global epoch: 5, step: 850000, train_cor_macbert_loss = 0.06658778458008603 Global epoch: 5, step: 850000, train_det_loss = 0.09456259771024307 Global epoch: 5, step: 850000, train_det_macbert_loss = 0.0931215572933781 Global epoch: 5, step: 850000, train_loss = 0.01622706025487412 Global epoch: 5, step: 860000, cor_acc = 0.7921330289946741 Global epoch: 5, step: 860000, cor_f1 = 0.7749121307115038 Global epoch: 5, step: 860000, cor_precision = 0.7947294071800867 Global epoch: 5, step: 860000, cor_recall = 0.7560591315630938 Global epoch: 5, step: 860000, det_acc = 0.8615075763825867 Global epoch: 5, step: 860000, det_f1 = 0.8647762895411799 Global epoch: 5, step: 860000, det_precision = 0.886891714160456 Global epoch: 5, step: 860000, det_recall = 0.8437369664952037 Global epoch: 5, step: 860000, eval_cor_loss = 0.007854211288166763 Global epoch: 5, step: 860000, eval_cor_macbert_loss = 0.020124237394936184 Global epoch: 5, step: 860000, eval_det_loss = 0.09617385686719498 Global epoch: 5, step: 860000, eval_det_macbert_loss = 0.09502427074408398 Global epoch: 5, step: 860000, eval_loss = 0.026230701163183975 Global epoch: 5, step: 860000, global_step = 860000 Global epoch: 5, step: 860000, lr = 3.4220767335773034e-06 Global epoch: 5, step: 860000, train_cor_loss = 0.17748570991875082 Global epoch: 5, step: 860000, train_cor_macbert_loss = 0.22291141929856992 Global epoch: 5, step: 860000, train_det_loss = 0.3165102150964811 Global epoch: 5, step: 860000, train_det_macbert_loss = 0.3116842253712722 Global epoch: 5, step: 860000, train_loss = 0.05432084243097248 Global epoch: 5, step: 870000, cor_acc = 0.7928847088157376 Global epoch: 5, step: 870000, cor_f1 = 0.7755491994920424 Global epoch: 5, step: 870000, cor_precision = 0.7949563270966643 Global epoch: 5, step: 870000, cor_recall = 0.7570670559340099 Global epoch: 5, step: 870000, det_acc = 0.8619567509098076 Global epoch: 5, step: 870000, det_f1 = 0.8649758482773354 Global epoch: 5, step: 870000, det_precision = 0.8866207634850733 Global epoch: 5, step: 870000, det_recall = 0.8443625747254275 Global epoch: 5, step: 870000, eval_cor_loss = 0.007812846267920935 Global epoch: 5, step: 870000, eval_cor_macbert_loss = 0.020068739582376288 Global epoch: 5, step: 870000, eval_det_loss = 0.09616968560798955 Global epoch: 5, step: 870000, eval_det_macbert_loss = 0.0950178191375956 Global epoch: 5, step: 870000, eval_loss = 0.026188737763311987 Global epoch: 5, step: 870000, global_step = 870000 Global epoch: 5, step: 870000, lr = 3.1548087621433185e-06 Global epoch: 5, step: 870000, train_cor_loss = 0.04268098432677699 Global epoch: 5, step: 870000, train_cor_macbert_loss = 0.05364255188527301 Global epoch: 5, step: 870000, train_det_loss = 0.07645503342522293 Global epoch: 5, step: 870000, train_det_macbert_loss = 0.07528775181738598 Global epoch: 5, step: 870000, train_loss = 0.013079553350351825 Global epoch: 5, step: 880000, cor_acc = 0.7919863597612958 Global epoch: 5, step: 880000, cor_f1 = 0.7749308383695663 Global epoch: 5, step: 880000, cor_precision = 0.7946791671739925 Global epoch: 5, step: 880000, cor_recall = 0.7561402289262709 Global epoch: 5, step: 880000, det_acc = 0.861003400892849 Global epoch: 5, step: 880000, det_f1 = 0.8643244719375943 Global epoch: 5, step: 880000, det_precision = 0.8863509070985024 Global epoch: 5, step: 880000, det_recall = 0.8433662356921081 Global epoch: 5, step: 880000, eval_cor_loss = 0.007811191964909755 Global epoch: 5, step: 880000, eval_cor_macbert_loss = 0.020076504058543974 Global epoch: 5, step: 880000, eval_det_loss = 0.09616594388534931 Global epoch: 5, step: 880000, eval_det_macbert_loss = 0.09501751306311401 Global epoch: 5, step: 880000, eval_loss = 0.02619103100931704 Global epoch: 5, step: 880000, global_step = 880000 Global epoch: 5, step: 880000, lr = 2.897176515379329e-06 Global epoch: 5, step: 880000, train_cor_loss = 0.09886677395474117 Global epoch: 5, step: 880000, train_cor_macbert_loss = 0.12425415292866304 Global epoch: 5, step: 880000, train_det_loss = 0.17686930828870928 Global epoch: 5, step: 880000, train_det_macbert_loss = 0.17416177822342147 Global epoch: 5, step: 880000, train_loss = 0.030288432280719747 Global epoch: 5, step: 890000, cor_acc = 0.7928113741990485 Global epoch: 5, step: 890000, cor_f1 = 0.7758653457819591 Global epoch: 5, step: 890000, cor_precision = 0.7960051672028858 Global epoch: 5, step: 890000, cor_recall = 0.7567194958061078 Global epoch: 5, step: 890000, det_acc = 0.8611684037803995 Global epoch: 5, step: 890000, det_f1 = 0.8644430190292923 Global epoch: 5, step: 890000, det_precision = 0.8868821292775665 Global epoch: 5, step: 890000, det_recall = 0.8431113582649798 Global epoch: 5, step: 890000, eval_cor_loss = 0.0077985765262229365 Global epoch: 5, step: 890000, eval_cor_macbert_loss = 0.020039658789525402 Global epoch: 5, step: 890000, eval_det_loss = 0.09616975868309184 Global epoch: 5, step: 890000, eval_det_macbert_loss = 0.09501816637047363 Global epoch: 5, step: 890000, eval_loss = 0.02617034526682169 Global epoch: 5, step: 890000, global_step = 890000 Global epoch: 5, step: 890000, lr = 2.649389569757849e-06 Global epoch: 5, step: 890000, train_cor_loss = 0.035883932091928666 Global epoch: 5, step: 890000, train_cor_macbert_loss = 0.04510973398250114 Global epoch: 5, step: 890000, train_det_loss = 0.064221664976152 Global epoch: 5, step: 890000, train_det_macbert_loss = 0.06323655873562899 Global epoch: 5, step: 890000, train_loss = 0.010995419053153543 Global epoch: 5, step: 900000, cor_acc = 0.7924263674614306 Global epoch: 5, step: 900000, cor_f1 = 0.7753184107974527 Global epoch: 5, step: 900000, cor_precision = 0.7956230187759084 Global epoch: 5, step: 900000, cor_recall = 0.7560243755503036 Global epoch: 5, step: 900000, det_acc = 0.8609667335845044 Global epoch: 5, step: 900000, det_f1 = 0.8641526470867789 Global epoch: 5, step: 900000, det_precision = 0.8867837112899293 Global epoch: 5, step: 900000, det_recall = 0.8426479447611104 Global epoch: 5, step: 900000, eval_cor_loss = 0.0078053244450463355 Global epoch: 5, step: 900000, eval_cor_macbert_loss = 0.020069230027874696 Global epoch: 5, step: 900000, eval_det_loss = 0.09616279975781165 Global epoch: 5, step: 900000, eval_det_macbert_loss = 0.09502285716733566 Global epoch: 5, step: 900000, eval_loss = 0.026185610787290453 Global epoch: 5, step: 900000, global_step = 900000 Global epoch: 5, step: 900000, lr = 2.411649492880189e-06 Global epoch: 5, step: 900000, train_cor_loss = 0.06832539909994088 Global epoch: 5, step: 900000, train_cor_macbert_loss = 0.0859627920677826 Global epoch: 5, step: 900000, train_det_loss = 0.12274524428474243 Global epoch: 5, step: 900000, train_det_macbert_loss = 0.12086870575452505 Global epoch: 5, step: 900000, train_loss = 0.020960882519096453 Global epoch: 5, step: 910000, cor_acc = 0.7939388939306438 Global epoch: 5, step: 910000, cor_f1 = 0.7769411960152601 Global epoch: 5, step: 910000, cor_precision = 0.7962591362934316 Global epoch: 5, step: 910000, cor_recall = 0.7585383938087956 Global epoch: 5, step: 910000, det_acc = 0.8627450980392157 Global epoch: 5, step: 910000, det_f1 = 0.8660104543054294 Global epoch: 5, step: 910000, det_precision = 0.887543021148771 Global epoch: 5, step: 910000, det_recall = 0.8454979378099078 Global epoch: 5, step: 910000, eval_cor_loss = 0.007748041215601313 Global epoch: 5, step: 910000, eval_cor_macbert_loss = 0.020003953343571298 Global epoch: 5, step: 910000, eval_det_loss = 0.09615895341250666 Global epoch: 5, step: 910000, eval_det_macbert_loss = 0.09501709713898457 Global epoch: 5, step: 910000, eval_loss = 0.026132802385318073 Global epoch: 5, step: 910000, global_step = 910000 Global epoch: 5, step: 910000, lr = 2.1841496795069584e-06 Global epoch: 5, step: 910000, train_cor_loss = 0.7687161870407587 Global epoch: 5, step: 910000, train_cor_macbert_loss = 0.9674243823994065 Global epoch: 5, step: 910000, train_det_loss = 1.3844933641128065 Global epoch: 5, step: 910000, train_det_macbert_loss = 1.3633160173234722 Global epoch: 5, step: 910000, train_loss = 0.23598636872018328 Global epoch: 5, step: 920000, cor_acc = 0.7933980511325615 Global epoch: 5, step: 920000, cor_f1 = 0.7763555334009841 Global epoch: 5, step: 920000, cor_precision = 0.7958076328819786 Global epoch: 5, step: 920000, cor_recall = 0.7578316882153946 Global epoch: 5, step: 920000, det_acc = 0.8620392523535828 Global epoch: 5, step: 920000, det_f1 = 0.8652270151264295 Global epoch: 5, step: 920000, det_precision = 0.8869058481453095 Global epoch: 5, step: 920000, det_recall = 0.8445826961397656 Global epoch: 5, step: 920000, eval_cor_loss = 0.0077673353325221055 Global epoch: 5, step: 920000, eval_cor_macbert_loss = 0.020015645880613622 Global epoch: 5, step: 920000, eval_det_loss = 0.09616161642824929 Global epoch: 5, step: 920000, eval_det_macbert_loss = 0.09501900303070233 Global epoch: 5, step: 920000, eval_loss = 0.02614631437909757 Global epoch: 5, step: 920000, global_step = 920000 Global epoch: 5, step: 920000, lr = 1.9670751942369488e-06 Global epoch: 5, step: 920000, train_cor_loss = 0.05252690276394594 Global epoch: 5, step: 920000, train_cor_macbert_loss = 0.06604182573139315 Global epoch: 5, step: 920000, train_det_loss = 0.0940610408804423 Global epoch: 5, step: 920000, train_det_macbert_loss = 0.0926187023632963 Global epoch: 5, step: 920000, train_loss = 0.016098173087540496 Global epoch: 5, step: 930000, cor_acc = 0.7935447203659397 Global epoch: 5, step: 930000, cor_f1 = 0.7766439303544608 Global epoch: 5, step: 930000, cor_precision = 0.7964011346896039 Global epoch: 5, step: 930000, cor_recall = 0.7578432735529913 Global epoch: 5, step: 930000, det_acc = 0.8619567509098076 Global epoch: 5, step: 930000, det_f1 = 0.8652502478436122 Global epoch: 5, step: 930000, det_precision = 0.8872615264740616 Global epoch: 5, step: 930000, det_recall = 0.8443046480374438 Global epoch: 5, step: 930000, eval_cor_loss = 0.007781110484356716 Global epoch: 5, step: 930000, eval_cor_macbert_loss = 0.020028391267314698 Global epoch: 5, step: 930000, eval_det_loss = 0.09616721239092761 Global epoch: 5, step: 930000, eval_det_macbert_loss = 0.09501798474755464 Global epoch: 5, step: 930000, eval_loss = 0.026157928917942528 Global epoch: 5, step: 930000, global_step = 930000 Global epoch: 5, step: 930000, lr = 1.7606026209623939e-06 Global epoch: 5, step: 930000, train_cor_loss = 0.17315507962279325 Global epoch: 5, step: 930000, train_cor_macbert_loss = 0.21781843788218178 Global epoch: 5, step: 930000, train_det_loss = 0.31093298709106215 Global epoch: 5, step: 930000, train_det_macbert_loss = 0.3061750351377231 Global epoch: 5, step: 930000, train_loss = 0.05311171328803577 Global epoch: 5, step: 940000, cor_acc = 0.7934713857492506 Global epoch: 5, step: 940000, cor_f1 = 0.7764936336924584 Global epoch: 5, step: 940000, cor_precision = 0.7961874155497937 Global epoch: 5, step: 940000, cor_recall = 0.7577505908522174 Global epoch: 5, step: 940000, det_acc = 0.8621309206244443 Global epoch: 5, step: 940000, det_f1 = 0.8654141809871486 Global epoch: 5, step: 940000, det_precision = 0.8873632058819949 Global epoch: 5, step: 940000, det_recall = 0.8445247694517818 Global epoch: 5, step: 940000, eval_cor_loss = 0.007760659229196417 Global epoch: 5, step: 940000, eval_cor_macbert_loss = 0.020024309878143895 Global epoch: 5, step: 940000, eval_det_loss = 0.09616188309175883 Global epoch: 5, step: 940000, eval_det_macbert_loss = 0.0950184411835335 Global epoch: 5, step: 940000, eval_loss = 0.02614713708286637 Global epoch: 5, step: 940000, global_step = 940000 Global epoch: 5, step: 940000, lr = 1.5648999192229936e-06 Global epoch: 5, step: 940000, train_cor_loss = 0.04217595227587933 Global epoch: 5, step: 940000, train_cor_macbert_loss = 0.053121677530690754 Global epoch: 5, step: 940000, train_det_loss = 0.07614430078241692 Global epoch: 5, step: 940000, train_det_macbert_loss = 0.07497620128489939 Global epoch: 5, step: 940000, train_loss = 0.012958882980569767 Global epoch: 6, step: 950000, cor_acc = 0.7865962654346451 Global epoch: 6, step: 950000, cor_f1 = 0.7758078300874657 Global epoch: 6, step: 950000, cor_precision = 0.8135463941115899 Global epoch: 6, step: 950000, cor_recall = 0.7414152648408174 Global epoch: 6, step: 950000, det_acc = 0.846208141975818 Global epoch: 6, step: 950000, det_f1 = 0.8546421059650016 Global epoch: 6, step: 950000, det_precision = 0.8962155015699884 Global epoch: 6, step: 950000, det_recall = 0.8167547152324018 Global epoch: 6, step: 950000, eval_cor_loss = 0.008180606903659704 Global epoch: 6, step: 950000, eval_cor_macbert_loss = 0.020456812231728003 Global epoch: 6, step: 950000, eval_det_loss = 0.09622721367700468 Global epoch: 6, step: 950000, eval_det_macbert_loss = 0.09511825404962952 Global epoch: 6, step: 950000, eval_loss = 0.026521814102429826 Global epoch: 6, step: 950000, global_step = 950000 Global epoch: 6, step: 950000, lr = 1.3801262875756365e-06 Global epoch: 6, step: 950000, train_cor_loss = 0.012835729512637077 Global epoch: 6, step: 950000, train_cor_macbert_loss = 0.02535938400274584 Global epoch: 6, step: 950000, train_det_loss = 0.09973564525015129 Global epoch: 6, step: 950000, train_det_macbert_loss = 0.09876148609536402 Global epoch: 6, step: 950000, train_loss = 0.007780052277459676 Global epoch: 6, step: 960000, cor_acc = 0.7853954110863607 Global epoch: 6, step: 960000, cor_f1 = 0.7752437061556683 Global epoch: 6, step: 960000, cor_precision = 0.8147684765540222 Global epoch: 6, step: 960000, cor_recall = 0.7393762454237917 Global epoch: 6, step: 960000, det_acc = 0.8441456058814363 Global epoch: 6, step: 960000, det_f1 = 0.8530960551489568 Global epoch: 6, step: 960000, det_precision = 0.8965900241289944 Global epoch: 6, step: 960000, det_recall = 0.8136266740812828 Global epoch: 6, step: 960000, eval_cor_loss = 0.008231568433615624 Global epoch: 6, step: 960000, eval_cor_macbert_loss = 0.020488583389423925 Global epoch: 6, step: 960000, eval_det_loss = 0.09624573086205203 Global epoch: 6, step: 960000, eval_det_macbert_loss = 0.0951284132930618 Global epoch: 6, step: 960000, eval_loss = 0.026559126229448355 Global epoch: 6, step: 960000, global_step = 960000 Global epoch: 6, step: 960000, lr = 1.206432034090918e-06 Global epoch: 6, step: 960000, train_cor_loss = 0.008047569337270268 Global epoch: 6, step: 960000, train_cor_macbert_loss = 0.015980497861253058 Global epoch: 6, step: 960000, train_det_loss = 0.06329590938643768 Global epoch: 6, step: 960000, train_det_macbert_loss = 0.06268182385803152 Global epoch: 6, step: 960000, train_loss = 0.004915064800753324 Global epoch: 6, step: 970000, cor_acc = 0.7853862442592745 Global epoch: 6, step: 970000, cor_f1 = 0.7756426618049225 Global epoch: 6, step: 970000, cor_precision = 0.8157067259759184 Global epoch: 6, step: 970000, cor_recall = 0.7393299040734047 Global epoch: 6, step: 970000, det_acc = 0.8433755924062004 Global epoch: 6, step: 970000, det_f1 = 0.8525311455484654 Global epoch: 6, step: 970000, det_precision = 0.8965667101260322 Global epoch: 6, step: 970000, det_recall = 0.8126187497103665 Global epoch: 6, step: 970000, eval_cor_loss = 0.008211753840480212 Global epoch: 6, step: 970000, eval_cor_macbert_loss = 0.02044368637149607 Global epoch: 6, step: 970000, eval_det_loss = 0.0962401787509879 Global epoch: 6, step: 970000, eval_det_macbert_loss = 0.09513033086849566 Global epoch: 6, step: 970000, eval_loss = 0.02653135124094865 Global epoch: 6, step: 970000, global_step = 970000 Global epoch: 6, step: 970000, lr = 1.0439584540818276e-06 Global epoch: 6, step: 970000, train_cor_loss = 0.015337875471035628 Global epoch: 6, step: 970000, train_cor_macbert_loss = 0.030452811472597697 Global epoch: 6, step: 970000, train_det_loss = 0.12051256536931788 Global epoch: 6, step: 970000, train_det_macbert_loss = 0.11933652312576688 Global epoch: 6, step: 970000, train_loss = 0.009362431205551348 Global epoch: 6, step: 980000, cor_acc = 0.7853862442592745 Global epoch: 6, step: 980000, cor_f1 = 0.7755397169713871 Global epoch: 6, step: 980000, cor_precision = 0.8154508631374503 Global epoch: 6, step: 980000, cor_recall = 0.7393530747485981 Global epoch: 6, step: 980000, det_acc = 0.8437147650083876 Global epoch: 6, step: 980000, det_f1 = 0.8528652241807786 Global epoch: 6, step: 980000, det_precision = 0.8967557276293429 Global epoch: 6, step: 980000, det_recall = 0.8130705778766393 Global epoch: 6, step: 980000, eval_cor_loss = 0.008229788301998055 Global epoch: 6, step: 980000, eval_cor_macbert_loss = 0.02048899109274088 Global epoch: 6, step: 980000, eval_det_loss = 0.09623866492887286 Global epoch: 6, step: 980000, eval_det_macbert_loss = 0.09513522531456069 Global epoch: 6, step: 980000, eval_loss = 0.026558523926129268 Global epoch: 6, step: 980000, global_step = 980000 Global epoch: 6, step: 980000, lr = 8.928377151640405e-07 Global epoch: 6, step: 980000, train_cor_loss = 0.16136878985332156 Global epoch: 6, step: 980000, train_cor_macbert_loss = 0.3207523534482285 Global epoch: 6, step: 980000, train_det_loss = 1.2718881810866092 Global epoch: 6, step: 980000, train_det_macbert_loss = 1.2595196822848278 Global epoch: 6, step: 980000, train_loss = 0.09868927217385609 Global epoch: 6, step: 990000, cor_acc = 0.7862295923511995 Global epoch: 6, step: 990000, cor_f1 = 0.7761871805145765 Global epoch: 6, step: 990000, cor_precision = 0.8153618530139537 Global epoch: 6, step: 990000, cor_recall = 0.7406042912090458 Global epoch: 6, step: 990000, det_acc = 0.844649781371174 Global epoch: 6, step: 990000, det_f1 = 0.8535679160747459 Global epoch: 6, step: 990000, det_precision = 0.8966480446927374 Global epoch: 6, step: 990000, det_recall = 0.8144376477130544 Global epoch: 6, step: 990000, eval_cor_loss = 0.008170121980190624 Global epoch: 6, step: 990000, eval_cor_macbert_loss = 0.020409131795331745 Global epoch: 6, step: 990000, eval_det_loss = 0.09623978531620993 Global epoch: 6, step: 990000, eval_det_macbert_loss = 0.09512272065631527 Global epoch: 6, step: 990000, eval_loss = 0.026498371696990278 Global epoch: 6, step: 990000, global_step = 990000 Global epoch: 6, step: 990000, lr = 7.531927497413332e-07 Global epoch: 6, step: 990000, train_cor_loss = 0.011686705521024387 Global epoch: 6, step: 990000, train_cor_macbert_loss = 0.023294804272425404 Global epoch: 6, step: 990000, train_det_loss = 0.09249587776535527 Global epoch: 6, step: 990000, train_det_macbert_loss = 0.09159853722099538 Global epoch: 6, step: 990000, train_loss = 0.007168555934361027 Global epoch: 6, step: 1000000, cor_acc = 0.7859545875386152 Global epoch: 6, step: 1000000, cor_f1 = 0.7761121504409727 Global epoch: 6, step: 1000000, cor_precision = 0.8157303370786517 Global epoch: 6, step: 1000000, cor_recall = 0.7401640483803698 Global epoch: 6, step: 1000000, det_acc = 0.844127272227264 Global epoch: 6, step: 1000000, det_f1 = 0.853203430598411 Global epoch: 6, step: 1000000, det_precision = 0.8967568947906026 Global epoch: 6, step: 1000000, det_recall = 0.8136846007692664 Global epoch: 6, step: 1000000, eval_cor_loss = 0.008183630192238354 Global epoch: 6, step: 1000000, eval_cor_macbert_loss = 0.020428662011151403 Global epoch: 6, step: 1000000, eval_det_loss = 0.09623463610441095 Global epoch: 6, step: 1000000, eval_det_macbert_loss = 0.09512293849678831 Global epoch: 6, step: 1000000, eval_loss = 0.026512043188566058 Global epoch: 6, step: 1000000, global_step = 1000000 Global epoch: 6, step: 1000000, lr = 6.251371550036072e-07 Global epoch: 6, step: 1000000, train_cor_loss = 0.038387274614829714 Global epoch: 6, step: 1000000, train_cor_macbert_loss = 0.07637057640792454 Global epoch: 6, step: 1000000, train_det_loss = 0.3023648914111046 Global epoch: 6, step: 1000000, train_det_macbert_loss = 0.2994057398463134 Global epoch: 6, step: 1000000, train_loss = 0.023476221778166603 Global epoch: 6, step: 1010000, cor_acc = 0.7867796019763679 Global epoch: 6, step: 1010000, cor_f1 = 0.7768213769743472 Global epoch: 6, step: 1010000, cor_precision = 0.8159190023207773 Global epoch: 6, step: 1010000, cor_recall = 0.7412994114648501 Global epoch: 6, step: 1010000, det_acc = 0.8453372934026345 Global epoch: 6, step: 1010000, det_f1 = 0.8543748254804598 Global epoch: 6, step: 1010000, det_precision = 0.8973757364004998 Global epoch: 6, step: 1010000, det_recall = 0.8153065480328097 Global epoch: 6, step: 1010000, eval_cor_loss = 0.008154157919489294 Global epoch: 6, step: 1010000, eval_cor_macbert_loss = 0.02041029438487825 Global epoch: 6, step: 1010000, eval_det_loss = 0.09623292414403248 Global epoch: 6, step: 1010000, eval_det_macbert_loss = 0.09512024973930064 Global epoch: 6, step: 1010000, eval_loss = 0.026491381182646306 Global epoch: 6, step: 1010000, global_step = 1010000 Global epoch: 6, step: 1010000, lr = 5.087751005187907e-07 Global epoch: 6, step: 1010000, train_cor_loss = 0.009399324952605856 Global epoch: 6, step: 1010000, train_cor_macbert_loss = 0.018800652362285307 Global epoch: 6, step: 1010000, train_det_loss = 0.07500936059357038 Global epoch: 6, step: 1010000, train_det_macbert_loss = 0.07428136229915568 Global epoch: 6, step: 1010000, train_loss = 0.005795448835953609 Global epoch: 6, step: 1020000, cor_acc = 0.786458763028353 Global epoch: 6, step: 1020000, cor_f1 = 0.7765828895514413 Global epoch: 6, step: 1020000, cor_precision = 0.8159684561103526 Global epoch: 6, step: 1020000, cor_recall = 0.7408244126233838 Global epoch: 6, step: 1020000, det_acc = 0.8449247861837582 Global epoch: 6, step: 1020000, det_f1 = 0.854040793524529 Global epoch: 6, step: 1020000, det_precision = 0.8973547539142751 Global epoch: 6, step: 1020000, det_recall = 0.8147156958153761 Global epoch: 6, step: 1020000, eval_cor_loss = 0.00815650485818785 Global epoch: 6, step: 1020000, eval_cor_macbert_loss = 0.020410147149905418 Global epoch: 6, step: 1020000, eval_det_loss = 0.0962292164153488 Global epoch: 6, step: 1020000, eval_det_macbert_loss = 0.09512025649309577 Global epoch: 6, step: 1020000, eval_loss = 0.026492038453928852 Global epoch: 6, step: 1020000, global_step = 1020000 Global epoch: 6, step: 1020000, lr = 4.0420124349389463e-07 Global epoch: 6, step: 1020000, train_cor_loss = 0.02185788431452126 Global epoch: 6, step: 1020000, train_cor_macbert_loss = 0.04340464259475708 Global epoch: 6, step: 1020000, train_det_loss = 0.1716420802076744 Global epoch: 6, step: 1020000, train_det_macbert_loss = 0.1699639443757049 Global epoch: 6, step: 1020000, train_loss = 0.013339256883301938 Global epoch: 6, step: 1030000, cor_acc = 0.7860829231178212 Global epoch: 6, step: 1030000, cor_f1 = 0.7764439879168769 Global epoch: 6, step: 1030000, cor_precision = 0.8166754037155899 Global epoch: 6, step: 1030000, cor_recall = 0.7399902683164188 Global epoch: 6, step: 1030000, det_acc = 0.8439714361667996 Global epoch: 6, step: 1030000, det_f1 = 0.8532095036073106 Global epoch: 6, step: 1030000, det_precision = 0.8974185216913222 Global epoch: 6, step: 1030000, det_recall = 0.8131516752398165 Global epoch: 6, step: 1030000, eval_cor_loss = 0.008191429285658974 Global epoch: 6, step: 1030000, eval_cor_macbert_loss = 0.020438125041676334 Global epoch: 6, step: 1030000, eval_det_loss = 0.09623835846777362 Global epoch: 6, step: 1030000, eval_det_macbert_loss = 0.09512596297818032 Global epoch: 6, step: 1030000, eval_loss = 0.026519885623614063 Global epoch: 6, step: 1030000, global_step = 1030000 Global epoch: 6, step: 1030000, lr = 3.115006517740654e-07 Global epoch: 6, step: 1030000, train_cor_loss = 0.0078990928953703 Global epoch: 6, step: 1030000, train_cor_macbert_loss = 0.01580714772340348 Global epoch: 6, step: 1030000, train_det_loss = 0.06305696146493367 Global epoch: 6, step: 1030000, train_det_macbert_loss = 0.06244534849626447 Global epoch: 6, step: 1030000, train_loss = 0.00487195653897615 Global epoch: 6, step: 1040000, cor_acc = 0.7864312625470946 Global epoch: 6, step: 1040000, cor_f1 = 0.7767488211559963 Global epoch: 6, step: 1040000, cor_precision = 0.8167714563206052 Global epoch: 6, step: 1040000, cor_recall = 0.740465267157885 Global epoch: 6, step: 1040000, det_acc = 0.8442739414606423 Global epoch: 6, step: 1040000, det_f1 = 0.8534344465509697 Global epoch: 6, step: 1040000, det_precision = 0.8974083729489342 Global epoch: 6, step: 1040000, det_recall = 0.813568747393299 Global epoch: 6, step: 1040000, eval_cor_loss = 0.008171234279410241 Global epoch: 6, step: 1040000, eval_cor_macbert_loss = 0.020418091901291048 Global epoch: 6, step: 1040000, eval_det_loss = 0.09623875806659102 Global epoch: 6, step: 1040000, eval_det_macbert_loss = 0.0951273181319796 Global epoch: 6, step: 1040000, eval_loss = 0.026502920249141197 Global epoch: 6, step: 1040000, global_step = 1040000 Global epoch: 6, step: 1040000, lr = 2.3074873464232926e-07 Global epoch: 6, step: 1040000, train_cor_loss = 0.015098347795526972 Global epoch: 6, step: 1040000, train_cor_macbert_loss = 0.030132950755753563 Global epoch: 6, step: 1040000, train_det_loss = 0.11973937131992948 Global epoch: 6, step: 1040000, train_det_macbert_loss = 0.11857313036519519 Global epoch: 6, step: 1040000, train_loss = 0.00927418518260346 Global epoch: 6, step: 1050000, cor_acc = 0.7862387591782857 Global epoch: 6, step: 1050000, cor_f1 = 0.7764518598631686 Global epoch: 6, step: 1050000, cor_precision = 0.816382592696701 Global epoch: 6, step: 1050000, cor_recall = 0.7402451457435469 Global epoch: 6, step: 1050000, det_acc = 0.844319775596073 Global epoch: 6, step: 1050000, det_f1 = 0.853446914000316 Global epoch: 6, step: 1050000, det_precision = 0.8973372856668285 Global epoch: 6, step: 1050000, det_recall = 0.8136498447564762 Global epoch: 6, step: 1050000, eval_cor_loss = 0.0081854749156993 Global epoch: 6, step: 1050000, eval_cor_macbert_loss = 0.020425681790926176 Global epoch: 6, step: 1050000, eval_det_loss = 0.0962393970800194 Global epoch: 6, step: 1050000, eval_det_macbert_loss = 0.09512693335132073 Global epoch: 6, step: 1050000, eval_loss = 0.026512217277901783 Global epoch: 6, step: 1050000, global_step = 1050000 Global epoch: 6, step: 1050000, lr = 1.6201118147629534e-07 Global epoch: 6, step: 1050000, train_cor_loss = 0.14859210272881201 Global epoch: 6, step: 1050000, train_cor_macbert_loss = 0.29748235986321536 Global epoch: 6, step: 1050000, train_det_loss = 1.187359798666485 Global epoch: 6, step: 1050000, train_det_macbert_loss = 1.175837921031475 Global epoch: 6, step: 1050000, train_loss = 0.0917053719108736 Global epoch: 6, step: 1060000, cor_acc = 0.7862845933137164 Global epoch: 6, step: 1060000, cor_f1 = 0.7763895553301465 Global epoch: 6, step: 1060000, cor_precision = 0.8160055156212096 Global epoch: 6, step: 1060000, cor_recall = 0.7404420964826915 Global epoch: 6, step: 1060000, det_acc = 0.8445947804086571 Global epoch: 6, step: 1060000, det_f1 = 0.8536616476047595 Global epoch: 6, step: 1060000, det_precision = 0.8972204844043257 Global epoch: 6, step: 1060000, det_recall = 0.8141364289355392 Global epoch: 6, step: 1060000, eval_cor_loss = 0.008163161160260463 Global epoch: 6, step: 1060000, eval_cor_macbert_loss = 0.020410351760191795 Global epoch: 6, step: 1060000, eval_det_loss = 0.0962360122819095 Global epoch: 6, step: 1060000, eval_det_macbert_loss = 0.09512341542131773 Global epoch: 6, step: 1060000, eval_loss = 0.026495700940703828 Global epoch: 6, step: 1060000, global_step = 1060000 Global epoch: 6, step: 1060000, lr = 1.0534390831171858e-07 Global epoch: 6, step: 1060000, train_cor_loss = 0.01162435864973033 Global epoch: 6, step: 1060000, train_cor_macbert_loss = 0.02317791109628187 Global epoch: 6, step: 1060000, train_det_loss = 0.09199931429590734 Global epoch: 6, step: 1060000, train_det_macbert_loss = 0.09110507620331125 Global epoch: 6, step: 1060000, train_loss = 0.007130948719465584 Global epoch: 6, step: 1070000, cor_acc = 0.7860187553282183 Global epoch: 6, step: 1070000, cor_f1 = 0.7763145900812484 Global epoch: 6, step: 1070000, cor_precision = 0.8163750463312074 Global epoch: 6, step: 1070000, cor_recall = 0.7400018536540155 Global epoch: 6, step: 1070000, det_acc = 0.8440997717460056 Global epoch: 6, step: 1070000, det_f1 = 0.853321341541229 Global epoch: 6, step: 1070000, det_precision = 0.8973556063956237 Global epoch: 6, step: 1070000, det_recall = 0.8134065526669447 Global epoch: 6, step: 1070000, eval_cor_loss = 0.008171480828384566 Global epoch: 6, step: 1070000, eval_cor_macbert_loss = 0.02041878196053432 Global epoch: 6, step: 1070000, eval_det_loss = 0.0962370541749445 Global epoch: 6, step: 1070000, eval_det_macbert_loss = 0.0951263673037806 Global epoch: 6, step: 1070000, eval_loss = 0.026503119202141222 Global epoch: 6, step: 1070000, global_step = 1070000 Global epoch: 6, step: 1070000, lr = 6.079301235640655e-08 Global epoch: 6, step: 1070000, train_cor_loss = 0.037103760130566925 Global epoch: 6, step: 1070000, train_cor_macbert_loss = 0.07438655707886985 Global epoch: 6, step: 1070000, train_det_loss = 0.29724236511603824 Global epoch: 6, step: 1070000, train_det_macbert_loss = 0.29437629726262626 Global epoch: 6, step: 1070000, train_loss = 0.022938696882152214 Global epoch: 6, step: 1080000, cor_acc = 0.7862937601408024 Global epoch: 6, step: 1080000, cor_f1 = 0.7765618069016644 Global epoch: 6, step: 1080000, cor_precision = 0.8165693328051321 Global epoch: 6, step: 1080000, cor_recall = 0.7402914870939339 Global epoch: 6, step: 1080000, det_acc = 0.8444206106940205 Global epoch: 6, step: 1080000, det_f1 = 0.8536237079887465 Global epoch: 6, step: 1080000, det_precision = 0.8976013699155304 Global epoch: 6, step: 1080000, det_recall = 0.8137541127948469 Global epoch: 6, step: 1080000, eval_cor_loss = 0.008165718184076074 Global epoch: 6, step: 1080000, eval_cor_macbert_loss = 0.0204144291226416 Global epoch: 6, step: 1080000, eval_det_loss = 0.09623564552156431 Global epoch: 6, step: 1080000, eval_det_macbert_loss = 0.09512479328508078 Global epoch: 6, step: 1080000, eval_loss = 0.02649859641576243 Global epoch: 6, step: 1080000, global_step = 1080000 Global epoch: 6, step: 1080000, lr = 2.8394734491458685e-08 Global epoch: 6, step: 1080000, train_cor_loss = 0.009424228153572403 Global epoch: 6, step: 1080000, train_cor_macbert_loss = 0.018804326139165745 Global epoch: 6, step: 1080000, train_det_loss = 0.0746937931742648 Global epoch: 6, step: 1080000, train_det_macbert_loss = 0.07396660021605082 Global epoch: 6, step: 1080000, train_loss = 0.0057866664594622775 Global epoch: 6, step: 1090000, cor_acc = 0.7862387591782857 Global epoch: 6, step: 1090000, cor_f1 = 0.7765515229598657 Global epoch: 6, step: 1090000, cor_precision = 0.8166734839963187 Global epoch: 6, step: 1090000, cor_recall = 0.7401872190555633 Global epoch: 6, step: 1090000, det_acc = 0.8442556078064699 Global epoch: 6, step: 1090000, det_f1 = 0.853477404769429 Global epoch: 6, step: 1090000, det_precision = 0.8975738828101033 Global epoch: 6, step: 1090000, det_recall = 0.8135108207053153 Global epoch: 6, step: 1090000, eval_cor_loss = 0.008171077306437374 Global epoch: 6, step: 1090000, eval_cor_macbert_loss = 0.02041869409566915 Global epoch: 6, step: 1090000, eval_det_loss = 0.09623652949549173 Global epoch: 6, step: 1090000, eval_det_macbert_loss = 0.09512572960092049 Global epoch: 6, step: 1090000, eval_loss = 0.02650282316060578 Global epoch: 6, step: 1090000, global_step = 1090000 Global epoch: 6, step: 1090000, lr = 8.175429790338585e-09 Global epoch: 6, step: 1090000, train_cor_loss = 0.021146108049744337 Global epoch: 6, step: 1090000, train_cor_macbert_loss = 0.042435541787029865 Global epoch: 6, step: 1090000, train_det_loss = 0.16990078759215754 Global epoch: 6, step: 1090000, train_det_macbert_loss = 0.16826516397561125 Global epoch: 6, step: 1090000, train_loss = 0.013096162320486656 Global epoch: 6, step: 1100000, cor_acc = 0.7862295923511995 Global epoch: 6, step: 1100000, cor_f1 = 0.7765326462151781 Global epoch: 6, step: 1100000, cor_precision = 0.8166317296385296 Global epoch: 6, step: 1100000, cor_recall = 0.7401872190555633 Global epoch: 6, step: 1100000, det_acc = 0.8442647746335561 Global epoch: 6, step: 1100000, det_f1 = 0.8534809665029899 Global epoch: 6, step: 1100000, det_precision = 0.8975535559077662 Global epoch: 6, step: 1100000, det_recall = 0.8135339913805089 Global epoch: 6, step: 1100000, eval_cor_loss = 0.008171643439283892 Global epoch: 6, step: 1100000, eval_cor_macbert_loss = 0.020419139783896072 Global epoch: 6, step: 1100000, eval_det_loss = 0.09623652096150803 Global epoch: 6, step: 1100000, eval_det_macbert_loss = 0.09512569989252216 Global epoch: 6, step: 1100000, eval_loss = 0.026503250313574915 Global epoch: 6, step: 1100000, global_step = 1100000 Global epoch: 6, step: 1100000, lr = 1.515460797818502e-10 Global epoch: 6, step: 1100000, train_cor_loss = 0.007845647729400232 Global epoch: 6, step: 1100000, train_cor_macbert_loss = 0.015719861564090765 Global epoch: 6, step: 1100000, train_det_loss = 0.06281746455112754 Global epoch: 6, step: 1100000, train_det_macbert_loss = 0.06221033815122776 Global epoch: 6, step: 1100000, train_loss = 0.004848106823010705