nerui-lora-r8-2

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:

• Loss: 0.0395
• Location Precision: 0.88
• Location Recall: 0.9462
• Location F1: 0.9119
• Location Number: 93
• Organization Precision: 0.9048
• Organization Recall: 0.9157
• Organization F1: 0.9102
• Organization Number: 166
• Person Precision: 0.9718
• Person Recall: 0.9718
• Person F1: 0.9718
• Person Number: 142
• Overall Precision: 0.9220
• Overall Recall: 0.9426
• Overall F1: 0.9322
• Overall Accuracy: 0.9874

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 16
• eval_batch_size: 64
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 100.0

Training results

Training Loss	Epoch	Step	Validation Loss	Location Precision	Location Recall	Location F1	Location Number	Organization Precision	Organization Recall	Organization F1	Organization Number	Person Precision	Person Recall	Person F1	Person Number	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
1.1704	1.0	96	0.7085	0.0	0.0	0.0	93	0.0	0.0	0.0	166	0.0	0.0	0.0	142	0.0	0.0	0.0	0.8343
0.668	2.0	192	0.5723	0.0	0.0	0.0	93	0.5	0.0060	0.0119	166	0.0	0.0	0.0	142	0.3333	0.0025	0.0050	0.8348
0.5537	3.0	288	0.4494	0.0	0.0	0.0	93	0.4167	0.0602	0.1053	166	0.2353	0.0563	0.0909	142	0.3	0.0449	0.0781	0.8455
0.4382	4.0	384	0.3281	0.2727	0.0645	0.1043	93	0.3710	0.2771	0.3172	166	0.3882	0.4648	0.4231	142	0.3734	0.2943	0.3291	0.8883
0.32	5.0	480	0.2350	0.3857	0.2903	0.3313	93	0.5231	0.6145	0.5651	166	0.5886	0.7254	0.6498	142	0.5273	0.5786	0.5517	0.9292
0.2426	6.0	576	0.1839	0.5745	0.5806	0.5775	93	0.6158	0.7530	0.6775	166	0.7636	0.8873	0.8208	142	0.6602	0.7606	0.7068	0.9512
0.1962	7.0	672	0.1463	0.7188	0.7419	0.7302	93	0.6804	0.7952	0.7333	166	0.8903	0.9718	0.9293	142	0.7618	0.8454	0.8014	0.9619
0.1696	8.0	768	0.1200	0.7732	0.8065	0.7895	93	0.7312	0.8193	0.7727	166	0.9133	0.9648	0.9384	142	0.8037	0.8678	0.8345	0.9682
0.1508	9.0	864	0.1069	0.8	0.8602	0.8290	93	0.7473	0.8373	0.7898	166	0.9079	0.9718	0.9388	142	0.8151	0.8903	0.8510	0.9695
0.1359	10.0	960	0.0937	0.7980	0.8495	0.8229	93	0.7581	0.8494	0.8011	166	0.9195	0.9648	0.9416	142	0.8226	0.8903	0.8551	0.9712
0.126	11.0	1056	0.0873	0.7843	0.8602	0.8205	93	0.7772	0.8614	0.8171	166	0.9133	0.9648	0.9384	142	0.8257	0.8978	0.8602	0.9726
0.1191	12.0	1152	0.0826	0.7885	0.8817	0.8325	93	0.7861	0.8855	0.8329	166	0.9195	0.9648	0.9416	142	0.8318	0.9127	0.8704	0.9739
0.1126	13.0	1248	0.0742	0.8235	0.9032	0.8615	93	0.8167	0.8855	0.8497	166	0.9320	0.9648	0.9481	142	0.8578	0.9177	0.8867	0.9770
0.1061	14.0	1344	0.0707	0.85	0.9140	0.8808	93	0.8439	0.8795	0.8614	166	0.9320	0.9648	0.9481	142	0.8762	0.9177	0.8965	0.9789
0.1003	15.0	1440	0.0703	0.86	0.9247	0.8912	93	0.8278	0.8976	0.8613	166	0.9448	0.9648	0.9547	142	0.8753	0.9277	0.9007	0.9783
0.1008	16.0	1536	0.0686	0.8529	0.9355	0.8923	93	0.8287	0.9036	0.8646	166	0.9320	0.9648	0.9481	142	0.8698	0.9327	0.9001	0.9778
0.0957	17.0	1632	0.0617	0.86	0.9247	0.8912	93	0.8613	0.8976	0.8791	166	0.9514	0.9648	0.9580	142	0.8921	0.9277	0.9095	0.9802
0.0923	18.0	1728	0.0594	0.8687	0.9247	0.8958	93	0.8713	0.8976	0.8843	166	0.9580	0.9648	0.9614	142	0.9007	0.9277	0.9140	0.9819
0.0894	19.0	1824	0.0591	0.8529	0.9355	0.8923	93	0.8497	0.8855	0.8673	166	0.9448	0.9648	0.9547	142	0.8833	0.9252	0.9038	0.9800
0.0852	20.0	1920	0.0565	0.8365	0.9355	0.8832	93	0.8690	0.8795	0.8743	166	0.9448	0.9648	0.9547	142	0.8873	0.9227	0.9046	0.9813
0.0857	21.0	2016	0.0591	0.8286	0.9355	0.8788	93	0.8514	0.8976	0.8739	166	0.9580	0.9648	0.9614	142	0.8818	0.9302	0.9053	0.9816
0.0817	22.0	2112	0.0585	0.8286	0.9355	0.8788	93	0.8506	0.8916	0.8706	166	0.9448	0.9648	0.9547	142	0.8774	0.9277	0.9018	0.9808
0.0792	23.0	2208	0.0544	0.8431	0.9247	0.8821	93	0.8675	0.8675	0.8675	166	0.9580	0.9648	0.9614	142	0.8929	0.9152	0.9039	0.9811
0.0788	24.0	2304	0.0548	0.8269	0.9247	0.8731	93	0.8675	0.8675	0.8675	166	0.9580	0.9648	0.9614	142	0.8886	0.9152	0.9017	0.9811
0.0772	25.0	2400	0.0541	0.8365	0.9355	0.8832	93	0.875	0.8855	0.8802	166	0.9514	0.9648	0.9580	142	0.8918	0.9252	0.9082	0.9816
0.0755	26.0	2496	0.0507	0.8776	0.9247	0.9005	93	0.8772	0.9036	0.8902	166	0.9514	0.9648	0.9580	142	0.9031	0.9302	0.9165	0.9835
0.0717	27.0	2592	0.0506	0.8687	0.9247	0.8958	93	0.8678	0.9096	0.8882	166	0.9580	0.9648	0.9614	142	0.8990	0.9327	0.9155	0.9841
0.0725	28.0	2688	0.0518	0.8350	0.9247	0.8776	93	0.8765	0.8976	0.8869	166	0.9718	0.9718	0.9718	142	0.8988	0.9302	0.9142	0.9833
0.0713	29.0	2784	0.0505	0.8431	0.9247	0.8821	93	0.8817	0.8976	0.8896	166	0.9580	0.9648	0.9614	142	0.8986	0.9277	0.9129	0.9833
0.0671	30.0	2880	0.0477	0.8687	0.9247	0.8958	93	0.8889	0.9157	0.9021	166	0.9718	0.9718	0.9718	142	0.9126	0.9377	0.9250	0.9846
0.0666	31.0	2976	0.0480	0.8350	0.9247	0.8776	93	0.8855	0.8855	0.8855	166	0.9718	0.9718	0.9718	142	0.9027	0.9252	0.9138	0.9838
0.0638	32.0	3072	0.0482	0.8515	0.9247	0.8866	93	0.8922	0.8976	0.8949	166	0.9718	0.9718	0.9718	142	0.9098	0.9302	0.9199	0.9844
0.0647	33.0	3168	0.0482	0.8350	0.9247	0.8776	93	0.8862	0.8916	0.8889	166	0.9718	0.9718	0.9718	142	0.9029	0.9277	0.9151	0.9835
0.0642	34.0	3264	0.0486	0.8431	0.9247	0.8821	93	0.8779	0.9096	0.8935	166	0.9650	0.9718	0.9684	142	0.8993	0.9352	0.9169	0.9833
0.0603	35.0	3360	0.0463	0.8515	0.9247	0.8866	93	0.8929	0.9036	0.8982	166	0.9718	0.9718	0.9718	142	0.9100	0.9327	0.9212	0.9852
0.0627	36.0	3456	0.0483	0.8350	0.9247	0.8776	93	0.8876	0.9036	0.8955	166	0.9718	0.9718	0.9718	142	0.9034	0.9327	0.9178	0.9846
0.0606	37.0	3552	0.0461	0.8776	0.9247	0.9005	93	0.8902	0.9277	0.9086	166	0.9718	0.9718	0.9718	142	0.9153	0.9426	0.9287	0.9855
0.0602	38.0	3648	0.0457	0.8958	0.9247	0.9101	93	0.8953	0.9277	0.9112	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9857
0.058	39.0	3744	0.0452	0.8866	0.9247	0.9053	93	0.8902	0.9277	0.9086	166	0.9718	0.9718	0.9718	142	0.9175	0.9426	0.9299	0.9860
0.0579	40.0	3840	0.0443	0.8958	0.9247	0.9101	93	0.9	0.9217	0.9107	166	0.9718	0.9718	0.9718	142	0.9240	0.9401	0.9320	0.9863
0.0551	41.0	3936	0.0439	0.8958	0.9247	0.9101	93	0.8960	0.9337	0.9145	166	0.9718	0.9718	0.9718	142	0.9221	0.9451	0.9335	0.9868
0.0568	42.0	4032	0.0435	0.8788	0.9355	0.9062	93	0.8941	0.9157	0.9048	166	0.9718	0.9718	0.9718	142	0.9173	0.9401	0.9286	0.9866
0.0557	43.0	4128	0.0440	0.8969	0.9355	0.9158	93	0.9042	0.9096	0.9069	166	0.9718	0.9718	0.9718	142	0.9261	0.9377	0.9318	0.9860
0.0582	44.0	4224	0.0446	0.8529	0.9355	0.8923	93	0.9024	0.8916	0.8970	166	0.9718	0.9718	0.9718	142	0.9142	0.9302	0.9221	0.9844
0.0548	45.0	4320	0.0424	0.8878	0.9355	0.9110	93	0.9107	0.9217	0.9162	166	0.9718	0.9718	0.9718	142	0.9265	0.9426	0.9345	0.9866
0.0533	46.0	4416	0.0424	0.8788	0.9355	0.9062	93	0.8988	0.9096	0.9042	166	0.9718	0.9718	0.9718	142	0.9193	0.9377	0.9284	0.9866
0.0516	47.0	4512	0.0428	0.8687	0.9247	0.8958	93	0.8864	0.9398	0.9123	166	0.9650	0.9718	0.9684	142	0.9091	0.9476	0.9280	0.9860
0.0501	48.0	4608	0.0430	0.8788	0.9355	0.9062	93	0.9042	0.9096	0.9069	166	0.9718	0.9718	0.9718	142	0.9216	0.9377	0.9295	0.9863
0.053	49.0	4704	0.0433	0.8788	0.9355	0.9062	93	0.9053	0.9217	0.9134	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9866
0.0483	50.0	4800	0.0416	0.9062	0.9355	0.9206	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9286	0.9401	0.9343	0.9871
0.0505	51.0	4896	0.0418	0.8980	0.9462	0.9215	93	0.9096	0.9096	0.9096	166	0.9718	0.9718	0.9718	142	0.9286	0.9401	0.9343	0.9866
0.05	52.0	4992	0.0403	0.9255	0.9355	0.9305	93	0.8895	0.9217	0.9053	166	0.9718	0.9718	0.9718	142	0.9265	0.9426	0.9345	0.9879
0.0493	53.0	5088	0.0422	0.8969	0.9355	0.9158	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9263	0.9401	0.9332	0.9860
0.0487	54.0	5184	0.0408	0.9158	0.9355	0.9255	93	0.9053	0.9217	0.9134	166	0.9718	0.9718	0.9718	142	0.9310	0.9426	0.9368	0.9877
0.0485	55.0	5280	0.0402	0.9158	0.9355	0.9255	93	0.9112	0.9277	0.9194	166	0.9718	0.9718	0.9718	142	0.9335	0.9451	0.9393	0.9874
0.0491	56.0	5376	0.0432	0.8878	0.9355	0.9110	93	0.8960	0.9337	0.9145	166	0.9718	0.9718	0.9718	142	0.9201	0.9476	0.9337	0.9863
0.0495	57.0	5472	0.0409	0.8980	0.9462	0.9215	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9265	0.9426	0.9345	0.9866
0.0495	58.0	5568	0.0425	0.8980	0.9462	0.9215	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9265	0.9426	0.9345	0.9866
0.0462	59.0	5664	0.0412	0.8980	0.9462	0.9215	93	0.9102	0.9157	0.9129	166	0.9718	0.9718	0.9718	142	0.9287	0.9426	0.9356	0.9871
0.048	60.0	5760	0.0409	0.9072	0.9462	0.9263	93	0.9157	0.9157	0.9157	166	0.9718	0.9718	0.9718	142	0.9333	0.9426	0.9380	0.9868
0.048	61.0	5856	0.0396	0.8980	0.9462	0.9215	93	0.9102	0.9157	0.9129	166	0.9718	0.9718	0.9718	142	0.9287	0.9426	0.9356	0.9879
0.0461	62.0	5952	0.0403	0.8969	0.9355	0.9158	93	0.8935	0.9096	0.9015	166	0.9718	0.9718	0.9718	142	0.9216	0.9377	0.9295	0.9871
0.0459	63.0	6048	0.0405	0.8889	0.9462	0.9167	93	0.9162	0.9217	0.9189	166	0.9718	0.9718	0.9718	142	0.9289	0.9451	0.9370	0.9871
0.0461	64.0	6144	0.0394	0.8969	0.9355	0.9158	93	0.8882	0.9096	0.8988	166	0.9718	0.9718	0.9718	142	0.9193	0.9377	0.9284	0.9874
0.0431	65.0	6240	0.0408	0.8980	0.9462	0.9215	93	0.9091	0.9036	0.9063	166	0.9718	0.9718	0.9718	142	0.9284	0.9377	0.9330	0.9874
0.0448	66.0	6336	0.0396	0.9072	0.9462	0.9263	93	0.9053	0.9217	0.9134	166	0.9718	0.9718	0.9718	142	0.9289	0.9451	0.9370	0.9877
0.044	67.0	6432	0.0403	0.8980	0.9462	0.9215	93	0.9091	0.9036	0.9063	166	0.9718	0.9718	0.9718	142	0.9284	0.9377	0.9330	0.9871
0.0439	68.0	6528	0.0404	0.8889	0.9462	0.9167	93	0.9207	0.9096	0.9152	166	0.9718	0.9718	0.9718	142	0.9309	0.9401	0.9355	0.9874
0.0451	69.0	6624	0.0416	0.88	0.9462	0.9119	93	0.9207	0.9096	0.9152	166	0.9718	0.9718	0.9718	142	0.9286	0.9401	0.9343	0.9868
0.0429	70.0	6720	0.0403	0.88	0.9462	0.9119	93	0.9053	0.9217	0.9134	166	0.9718	0.9718	0.9718	142	0.9221	0.9451	0.9335	0.9877
0.0447	71.0	6816	0.0402	0.8980	0.9462	0.9215	93	0.9167	0.9277	0.9222	166	0.9718	0.9718	0.9718	142	0.9314	0.9476	0.9394	0.9877
0.0437	72.0	6912	0.0398	0.8889	0.9462	0.9167	93	0.9152	0.9096	0.9124	166	0.9718	0.9718	0.9718	142	0.9286	0.9401	0.9343	0.9871
0.041	73.0	7008	0.0399	0.8878	0.9355	0.9110	93	0.9107	0.9217	0.9162	166	0.9718	0.9718	0.9718	142	0.9265	0.9426	0.9345	0.9874
0.0425	74.0	7104	0.0406	0.8969	0.9355	0.9158	93	0.9112	0.9277	0.9194	166	0.9718	0.9718	0.9718	142	0.9289	0.9451	0.9370	0.9871
0.0426	75.0	7200	0.0395	0.8878	0.9355	0.9110	93	0.9	0.9217	0.9107	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9871
0.0398	76.0	7296	0.0402	0.8889	0.9462	0.9167	93	0.9212	0.9157	0.9184	166	0.9718	0.9718	0.9718	142	0.9310	0.9426	0.9368	0.9874
0.0407	77.0	7392	0.0392	0.8788	0.9355	0.9062	93	0.9096	0.9096	0.9096	166	0.9718	0.9718	0.9718	142	0.9238	0.9377	0.9307	0.9874
0.0411	78.0	7488	0.0394	0.8788	0.9355	0.9062	93	0.8988	0.9096	0.9042	166	0.9718	0.9718	0.9718	142	0.9193	0.9377	0.9284	0.9868
0.0417	79.0	7584	0.0395	0.8788	0.9355	0.9062	93	0.9053	0.9217	0.9134	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9871
0.0412	80.0	7680	0.0396	0.8788	0.9355	0.9062	93	0.8895	0.9217	0.9053	166	0.9718	0.9718	0.9718	142	0.9153	0.9426	0.9287	0.9877
0.0431	81.0	7776	0.0399	0.87	0.9355	0.9016	93	0.8941	0.9157	0.9048	166	0.9718	0.9718	0.9718	142	0.9150	0.9401	0.9274	0.9871
0.042	82.0	7872	0.0401	0.8889	0.9462	0.9167	93	0.9162	0.9217	0.9189	166	0.9718	0.9718	0.9718	142	0.9289	0.9451	0.9370	0.9871
0.0412	83.0	7968	0.0403	0.8889	0.9462	0.9167	93	0.9162	0.9217	0.9189	166	0.9718	0.9718	0.9718	142	0.9289	0.9451	0.9370	0.9871
0.0413	84.0	8064	0.0409	0.8889	0.9462	0.9167	93	0.9102	0.9157	0.9129	166	0.9718	0.9718	0.9718	142	0.9265	0.9426	0.9345	0.9871
0.0405	85.0	8160	0.0397	0.8713	0.9462	0.9072	93	0.9107	0.9217	0.9162	166	0.9718	0.9718	0.9718	142	0.9221	0.9451	0.9335	0.9879
0.0405	86.0	8256	0.0397	0.8713	0.9462	0.9072	93	0.9107	0.9217	0.9162	166	0.9718	0.9718	0.9718	142	0.9221	0.9451	0.9335	0.9879
0.0401	87.0	8352	0.0398	0.8713	0.9462	0.9072	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9197	0.9426	0.9310	0.9877
0.041	88.0	8448	0.0398	0.8713	0.9462	0.9072	93	0.9107	0.9217	0.9162	166	0.9718	0.9718	0.9718	142	0.9221	0.9451	0.9335	0.9879
0.0397	89.0	8544	0.0396	0.87	0.9355	0.9016	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9195	0.9401	0.9297	0.9877
0.0398	90.0	8640	0.0396	0.87	0.9355	0.9016	93	0.9053	0.9217	0.9134	166	0.9718	0.9718	0.9718	142	0.9197	0.9426	0.9310	0.9879
0.039	91.0	8736	0.0395	0.88	0.9462	0.9119	93	0.9162	0.9217	0.9189	166	0.9718	0.9718	0.9718	142	0.9267	0.9451	0.9358	0.9877
0.0385	92.0	8832	0.0398	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9871
0.0385	93.0	8928	0.0398	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9874
0.0398	94.0	9024	0.0397	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9871
0.0382	95.0	9120	0.0396	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9874
0.0408	96.0	9216	0.0394	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9874
0.0372	97.0	9312	0.0395	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9871
0.0392	98.0	9408	0.0395	0.8788	0.9355	0.9062	93	0.8994	0.9157	0.9075	166	0.9718	0.9718	0.9718	142	0.9195	0.9401	0.9297	0.9871
0.0393	99.0	9504	0.0395	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9874
0.0399	100.0	9600	0.0395	0.88	0.9462	0.9119	93	0.9048	0.9157	0.9102	166	0.9718	0.9718	0.9718	142	0.9220	0.9426	0.9322	0.9874

Framework versions

• Transformers 4.39.3
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.15.2