sentiment-pt-pl10-4

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
0.5514	1.0	122	0.5084	0.7218	0.6601	0.6507	0.6546
0.4753	2.0	244	0.4007	0.8170	0.7870	0.7530	0.7662
0.3834	3.0	366	0.3542	0.8396	0.8449	0.7540	0.7805
0.3188	4.0	488	0.3214	0.8622	0.8342	0.8325	0.8333
0.2981	5.0	610	0.2984	0.8822	0.8624	0.8492	0.8553
0.2835	6.0	732	0.2810	0.8697	0.8520	0.8253	0.8368
0.2517	7.0	854	0.2866	0.8872	0.8672	0.8577	0.8622
0.2374	8.0	976	0.2997	0.8797	0.8671	0.8349	0.8485
0.2293	9.0	1098	0.2909	0.8797	0.8600	0.8449	0.8518
0.2091	10.0	1220	0.2928	0.8822	0.8564	0.8617	0.8590
0.198	11.0	1342	0.2847	0.8797	0.8522	0.8624	0.8570
0.1906	12.0	1464	0.3120	0.8747	0.8586	0.8313	0.8431
0.1818	13.0	1586	0.2906	0.8772	0.8535	0.8481	0.8507
0.1756	14.0	1708	0.2810	0.8772	0.8524	0.8506	0.8515
0.174	15.0	1830	0.2829	0.8847	0.8634	0.8559	0.8595
0.1705	16.0	1952	0.2922	0.8822	0.8624	0.8492	0.8553
0.1509	17.0	2074	0.2991	0.8822	0.8596	0.8542	0.8568
0.1549	18.0	2196	0.3000	0.8822	0.8624	0.8492	0.8553
0.1469	19.0	2318	0.2943	0.8847	0.8609	0.8609	0.8609
0.1493	20.0	2440	0.3026	0.8822	0.8624	0.8492	0.8553