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apwic/
sentiment-lora-r8a1d0.05-0

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sentiment-lora-r8a1d0.05-0

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
0.5609	1.0	122	0.5086	0.7193	0.6580	0.6514	0.6543
0.4986	2.0	244	0.4855	0.7494	0.7127	0.7427	0.7201
0.4593	3.0	366	0.4238	0.7694	0.7249	0.7394	0.7309
0.3957	4.0	488	0.3916	0.8070	0.7670	0.7735	0.7700
0.3658	5.0	610	0.4266	0.7995	0.7641	0.7981	0.7744
0.3345	6.0	732	0.3666	0.8371	0.8028	0.8072	0.8049
0.3237	7.0	854	0.3714	0.8396	0.8045	0.8265	0.8136
0.304	8.0	976	0.3537	0.8421	0.8083	0.8158	0.8119
0.3027	9.0	1098	0.3531	0.8446	0.8111	0.8201	0.8153
0.2962	10.0	1220	0.3382	0.8521	0.8220	0.8204	0.8212
0.2721	11.0	1342	0.3490	0.8496	0.8162	0.8311	0.8229
0.2693	12.0	1464	0.3502	0.8546	0.8220	0.8372	0.8288
0.2745	13.0	1586	0.3284	0.8571	0.8289	0.8239	0.8264
0.2712	14.0	1708	0.3297	0.8596	0.8299	0.8332	0.8315
0.256	15.0	1830	0.3357	0.8647	0.8346	0.8442	0.8391
0.2504	16.0	1952	0.3346	0.8571	0.8255	0.8364	0.8306
0.2487	17.0	2074	0.3242	0.8571	0.8281	0.8264	0.8272
0.2514	18.0	2196	0.3309	0.8622	0.8314	0.8425	0.8365
0.2451	19.0	2318	0.3243	0.8622	0.8333	0.8350	0.8341
0.2461	20.0	2440	0.3260	0.8622	0.8319	0.8400	0.8357