sentiment-lora-r2a2d0.1-0

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
0.5634	1.0	122	0.5108	0.7193	0.6572	0.6489	0.6524
0.5081	2.0	244	0.5049	0.7218	0.6829	0.7082	0.6888
0.4924	3.0	366	0.4667	0.7494	0.6977	0.6977	0.6977
0.4698	4.0	488	0.4392	0.7794	0.7349	0.7114	0.7207
0.4519	5.0	610	0.4548	0.7469	0.7169	0.7534	0.7226
0.4356	6.0	732	0.4111	0.8145	0.7770	0.7713	0.7740
0.421	7.0	854	0.4101	0.7945	0.7538	0.7721	0.7612
0.4039	8.0	976	0.3829	0.8296	0.7949	0.7919	0.7934
0.3887	9.0	1098	0.3800	0.8321	0.7972	0.7987	0.7979
0.3797	10.0	1220	0.3768	0.8371	0.8044	0.7997	0.8020
0.368	11.0	1342	0.3842	0.8221	0.7846	0.8016	0.7918
0.3598	12.0	1464	0.3778	0.8271	0.7902	0.8051	0.7968
0.3548	13.0	1586	0.3624	0.8471	0.8167	0.8118	0.8142
0.3469	14.0	1708	0.3637	0.8446	0.8120	0.8151	0.8135
0.3431	15.0	1830	0.3685	0.8396	0.8049	0.8165	0.8102
0.3275	16.0	1952	0.3664	0.8371	0.8017	0.8172	0.8086
0.3288	17.0	2074	0.3590	0.8396	0.8055	0.8115	0.8084
0.3335	18.0	2196	0.3607	0.8471	0.8138	0.8243	0.8187
0.3239	19.0	2318	0.3613	0.8446	0.8107	0.8226	0.8161
0.327	20.0	2440	0.3608	0.8471	0.8138	0.8243	0.8187