sentiment-lora-r2a1d0.05-1

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
0.5663	1.0	122	0.5216	0.7293	0.6677	0.6510	0.6572
0.5149	2.0	244	0.5134	0.7243	0.6758	0.6899	0.6810
0.4925	3.0	366	0.4821	0.7569	0.7055	0.6980	0.7014
0.4608	4.0	488	0.4654	0.7644	0.7150	0.7083	0.7114
0.4493	5.0	610	0.4600	0.7569	0.7126	0.7305	0.7193
0.4257	6.0	732	0.4307	0.7870	0.7433	0.7318	0.7369
0.4178	7.0	854	0.4181	0.7970	0.7552	0.7614	0.7581
0.3977	8.0	976	0.3972	0.8070	0.7687	0.7560	0.7617
0.3946	9.0	1098	0.3937	0.8145	0.7779	0.7663	0.7716
0.3762	10.0	1220	0.3874	0.8246	0.7995	0.7584	0.7738
0.3727	11.0	1342	0.3787	0.8321	0.8014	0.7837	0.7915
0.3626	12.0	1464	0.3750	0.8371	0.8059	0.7947	0.7999
0.359	13.0	1586	0.3728	0.8296	0.8066	0.7644	0.7803
0.3488	14.0	1708	0.3709	0.8296	0.8049	0.7669	0.7816
0.3445	15.0	1830	0.3667	0.8421	0.8131	0.7983	0.8050
0.3344	16.0	1952	0.3656	0.8421	0.8142	0.7958	0.8040
0.3339	17.0	2074	0.3654	0.8396	0.8128	0.7890	0.7992
0.3357	18.0	2196	0.3638	0.8421	0.8154	0.7933	0.8029
0.3357	19.0	2318	0.3646	0.8421	0.8154	0.7933	0.8029
0.3359	20.0	2440	0.3638	0.8446	0.8193	0.7951	0.8055