SST2_XLNet_5E

This model is a fine-tuned version of xlnet-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

Model description

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6038	0.12	50	0.2830	0.8933
0.3903	0.23	100	0.3346	0.9
0.3476	0.35	150	0.4187	0.8533
0.3528	0.46	200	0.3177	0.9
0.3372	0.58	250	0.4171	0.8333
0.3106	0.69	300	0.2825	0.9
0.295	0.81	350	0.3152	0.9
0.2828	0.92	400	0.4360	0.88
0.2359	1.04	450	0.3971	0.9
0.2224	1.15	500	0.3380	0.88
0.2136	1.27	550	0.3889	0.8933
0.264	1.39	600	0.4182	0.8667
0.1864	1.5	650	0.4887	0.88
0.1817	1.62	700	0.3626	0.9133
0.2021	1.73	750	0.4481	0.8933
0.2154	1.85	800	0.3702	0.8933
0.2392	1.96	850	0.5025	0.8933
0.1496	2.08	900	0.4606	0.9133
0.1537	2.19	950	0.5008	0.8933
0.1015	2.31	1000	0.5612	0.9067
0.0915	2.42	1050	0.5249	0.8933
0.1239	2.54	1100	0.4234	0.9133
0.1135	2.66	1150	0.4910	0.9067
0.1738	2.77	1200	0.3844	0.92
0.1428	2.89	1250	0.4282	0.92
0.1282	3.0	1300	0.4320	0.9
0.059	3.12	1350	0.4957	0.9133
0.0517	3.23	1400	0.4927	0.92
0.0853	3.35	1450	0.4187	0.92
0.0808	3.46	1500	0.4304	0.92
0.09	3.58	1550	0.3447	0.9267
0.044	3.7	1600	0.4994	0.9067
0.0443	3.81	1650	0.4516	0.9133
0.0974	3.93	1700	0.4172	0.92
0.0768	4.04	1750	0.4777	0.9133
0.0418	4.16	1800	0.4924	0.9267
0.0237	4.27	1850	0.5254	0.92
0.0426	4.39	1900	0.5532	0.9133
0.0336	4.5	1950	0.5838	0.9067
0.0188	4.62	2000	0.5775	0.9067
0.0318	4.73	2050	0.5781	0.9067
0.0348	4.85	2100	0.5526	0.9133
0.0524	4.97	2150	0.5502	0.9133