sentiment-lora-r2a0d0.15-0

This model is a fine-tuned version of indolem/indobert-base-uncased 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	Precision	Recall	F1
0.563	1.0	122	0.5138	0.7243	0.6636	0.6549	0.6586
0.509	2.0	244	0.5057	0.7168	0.6763	0.6996	0.6820
0.4924	3.0	366	0.4708	0.7393	0.6877	0.6931	0.6901
0.468	4.0	488	0.4379	0.7845	0.7412	0.7200	0.7286
0.4495	5.0	610	0.4466	0.7594	0.7233	0.7548	0.7313
0.4334	6.0	732	0.4041	0.8271	0.7927	0.7851	0.7887
0.415	7.0	854	0.4057	0.7995	0.7590	0.7756	0.7660
0.3974	8.0	976	0.3852	0.8321	0.7982	0.7937	0.7959
0.3849	9.0	1098	0.3829	0.8246	0.7880	0.7909	0.7894
0.3771	10.0	1220	0.3786	0.8396	0.8065	0.8065	0.8065
0.3633	11.0	1342	0.3843	0.8296	0.7931	0.8069	0.7993
0.3591	12.0	1464	0.3833	0.8296	0.7931	0.8069	0.7993
0.354	13.0	1586	0.3705	0.8396	0.8065	0.8065	0.8065
0.3451	14.0	1708	0.3709	0.8371	0.8028	0.8072	0.8049
0.3403	15.0	1830	0.3733	0.8321	0.7960	0.8112	0.8027
0.3282	16.0	1952	0.3715	0.8346	0.7988	0.8155	0.8061
0.3286	17.0	2074	0.3664	0.8321	0.7965	0.8037	0.7999
0.3348	18.0	2196	0.3670	0.8271	0.7904	0.8001	0.7949
0.325	19.0	2318	0.3669	0.8321	0.7961	0.8087	0.8018
0.3266	20.0	2440	0.3672	0.8321	0.7961	0.8087	0.8018