Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Combined Score
0.3017	1.0	1959	0.2241	0.9608	0.9713	0.9661
0.233	2.0	3918	0.2357	0.9828	0.9876	0.9852
0.2241	3.0	5877	0.1908	0.9706	0.9786	0.9746
0.2189	4.0	7836	0.1863	0.9755	0.9824	0.9789
0.2149	5.0	9795	0.1868	0.9804	0.9858	0.9831
0.211	6.0	11754	0.1735	0.9804	0.9859	0.9831
0.2073	7.0	13713	0.1875	0.9828	0.9876	0.9852
0.204	8.0	15672	0.1690	0.9853	0.9894	0.9873
0.2014	9.0	17631	0.1597	0.9853	0.9893	0.9873
0.1992	10.0	19590	0.1604	0.9877	0.9911	0.9894
0.1975	11.0	21549	0.1563	0.9853	0.9894	0.9873
0.1959	12.0	23508	0.1518	0.9853	0.9894	0.9873
0.1948	13.0	25467	0.1429	0.9902	0.9929	0.9915
0.1937	14.0	27426	0.1484	0.9853	0.9894	0.9873
0.1928	15.0	29385	0.1527	0.9804	0.9856	0.9830
0.1919	16.0	31344	0.1433	0.9926	0.9947	0.9936
0.1913	17.0	33303	0.1445	0.9902	0.9929	0.9915
0.1905	18.0	35262	0.1407	0.9926	0.9947	0.9936
0.1899	19.0	37221	0.1402	0.9926	0.9947	0.9936
0.1892	20.0	39180	0.1387	0.9926	0.9947	0.9936
0.1887	21.0	41139	0.1384	0.9926	0.9947	0.9936
0.1882	22.0	43098	0.1430	0.9951	0.9964	0.9958
0.1877	23.0	45057	0.1384	0.9951	0.9964	0.9958
0.1871	24.0	47016	0.1398	0.9951	0.9964	0.9958
0.1867	25.0	48975	0.1336	0.9926	0.9947	0.9936
0.1863	26.0	50934	0.1368	0.9951	0.9964	0.9958
0.1859	27.0	52893	0.1337	0.9951	0.9964	0.9958
0.1855	28.0	54852	0.1352	0.9926	0.9947	0.9936
0.1851	29.0	56811	0.1314	0.9951	0.9964	0.9958
0.1847	30.0	58770	0.1333	0.9951	0.9964	0.9958
0.1844	31.0	60729	0.1368	0.9951	0.9964	0.9958
0.184	32.0	62688	0.1310	0.9951	0.9964	0.9958
0.1837	33.0	64647	0.1321	0.9951	0.9964	0.9958
0.1834	34.0	66606	0.1302	0.9926	0.9947	0.9936
0.183	35.0	68565	0.1320	0.9951	0.9964	0.9958
0.1827	36.0	70524	0.1303	0.9951	0.9964	0.9958
0.1825	37.0	72483	0.1273	0.9951	0.9964	0.9958
0.1822	38.0	74442	0.1293	0.9951	0.9964	0.9958
0.1819	39.0	76401	0.1296	0.9951	0.9964	0.9958
0.1817	40.0	78360	0.1305	0.9926	0.9947	0.9936
0.1814	41.0	80319	0.1267	0.9926	0.9947	0.9936
0.1812	42.0	82278	0.1267	0.9951	0.9964	0.9958
0.1809	43.0	84237	0.1278	0.9902	0.9929	0.9915
0.1807	44.0	86196	0.1293	0.9951	0.9964	0.9958
0.1805	45.0	88155	0.1269	0.9951	0.9964	0.9958
0.1803	46.0	90114	0.1284	0.9951	0.9964	0.9958

Framework versions

Transformers 4.26.0
Pytorch 1.14.0a0+410ce96
Datasets 2.9.0
Tokenizers 0.13.2

gokuls/mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256

mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokuls/
mobilebert_sa_GLUE_Experiment_logit_kd_data_aug_mrpc_256