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apwic/
sentiment-lora-r8-0

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sentiment-lora-r8-0

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:

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The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.5593	1.0	122	0.4990	0.7243	0.6593	0.6374	0.6446
0.4939	2.0	244	0.4696	0.7619	0.7265	0.7590	0.7346
0.4469	3.0	366	0.4036	0.8070	0.7670	0.7760	0.7711
0.3781	4.0	488	0.3748	0.8195	0.7827	0.7798	0.7812
0.3532	5.0	610	0.4110	0.8045	0.7687	0.8017	0.7792
0.3273	6.0	732	0.3612	0.8321	0.7960	0.8137	0.8036
0.3098	7.0	854	0.3552	0.8371	0.8017	0.8197	0.8094
0.2953	8.0	976	0.3438	0.8546	0.8239	0.8272	0.8255
0.28	9.0	1098	0.3590	0.8446	0.8102	0.8301	0.8186
0.2701	10.0	1220	0.3354	0.8571	0.8299	0.8214	0.8255
0.2694	11.0	1342	0.3366	0.8571	0.8281	0.8264	0.8272
0.2657	12.0	1464	0.3378	0.8596	0.8287	0.8382	0.8332
0.2603	13.0	1586	0.3295	0.8647	0.8377	0.8342	0.8359
0.2564	14.0	1708	0.3318	0.8596	0.8299	0.8332	0.8315
0.2583	15.0	1830	0.3291	0.8596	0.8299	0.8332	0.8315
0.2438	16.0	1952	0.3323	0.8571	0.8260	0.8339	0.8298
0.2465	17.0	2074	0.3225	0.8546	0.8273	0.8171	0.8219
0.2494	18.0	2196	0.3292	0.8571	0.8266	0.8314	0.8289
0.2382	19.0	2318	0.3246	0.8571	0.8273	0.8289	0.8281
0.236	20.0	2440	0.3235	0.8596	0.8307	0.8307	0.8307