nerui-lora-r16-3

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: 0.0458
• Location Precision: 0.9022
• Location Recall: 0.9651
• Location F1: 0.9326
• Location Number: 86
• Organization Precision: 0.9314
• Organization Recall: 0.9157
• Organization F1: 0.9235
• Organization Number: 178
• Person Precision: 0.9843
• Person Recall: 0.9766
• Person F1: 0.9804
• Person Number: 128
• Overall Precision: 0.9416
• Overall Recall: 0.9464
• Overall F1: 0.9440
• Overall Accuracy: 0.9884

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
1.0611	1.0	96	0.6536	0.0	0.0	0.0	86	0.0	0.0	0.0	178	0.0	0.0	0.0	128	0.0	0.0	0.0	0.8435
0.6324	2.0	192	0.5023	0.0	0.0	0.0	86	0.5556	0.0281	0.0535	178	0.0	0.0	0.0	128	0.4167	0.0128	0.0248	0.8448
0.4878	3.0	288	0.3482	0.25	0.0233	0.0426	86	0.3936	0.2079	0.2721	178	0.3543	0.3516	0.3529	128	0.3668	0.2143	0.2705	0.8799
0.341	4.0	384	0.2386	0.5185	0.3256	0.4	86	0.5308	0.6292	0.5758	178	0.5767	0.7344	0.6460	128	0.5467	0.5969	0.5707	0.9296
0.2391	5.0	480	0.1745	0.7179	0.6512	0.6829	86	0.6603	0.7753	0.7132	178	0.8151	0.9297	0.8686	128	0.7229	0.7985	0.7588	0.9547
0.1867	6.0	576	0.1380	0.7396	0.8256	0.7802	86	0.7385	0.8090	0.7721	178	0.9118	0.9688	0.9394	128	0.7939	0.8648	0.8278	0.9655
0.1578	7.0	672	0.1150	0.75	0.8372	0.7912	86	0.7755	0.8539	0.8128	178	0.9058	0.9766	0.9398	128	0.8116	0.8903	0.8491	0.9690
0.1374	8.0	768	0.0980	0.7766	0.8488	0.8111	86	0.8105	0.8652	0.8370	178	0.9191	0.9766	0.9470	128	0.8381	0.8980	0.8670	0.9730
0.1267	9.0	864	0.0882	0.77	0.8953	0.8280	86	0.8511	0.8989	0.8743	178	0.9328	0.9766	0.9542	128	0.8578	0.9235	0.8894	0.9749
0.115	10.0	960	0.0822	0.8061	0.9186	0.8587	86	0.8474	0.9045	0.8750	178	0.9328	0.9766	0.9542	128	0.8649	0.9311	0.8968	0.9765
0.1082	11.0	1056	0.0755	0.7835	0.8837	0.8306	86	0.8495	0.8876	0.8681	178	0.9466	0.9688	0.9575	128	0.8647	0.9133	0.8883	0.9768
0.1032	12.0	1152	0.0724	0.8495	0.9186	0.8827	86	0.8579	0.9157	0.8859	178	0.9323	0.9688	0.9502	128	0.8798	0.9337	0.9059	0.9781
0.0944	13.0	1248	0.0646	0.8778	0.9186	0.8977	86	0.875	0.9045	0.8895	178	0.9466	0.9688	0.9575	128	0.8988	0.9286	0.9134	0.9800
0.0923	14.0	1344	0.0638	0.8242	0.8721	0.8475	86	0.8743	0.8989	0.8864	178	0.9538	0.9688	0.9612	128	0.8886	0.9158	0.9020	0.9798
0.0918	15.0	1440	0.0623	0.8571	0.9070	0.8814	86	0.8859	0.9157	0.9006	178	0.9615	0.9766	0.9690	128	0.9037	0.9337	0.9184	0.9806
0.0848	16.0	1536	0.0615	0.8298	0.9070	0.8667	86	0.8696	0.8989	0.8840	178	0.9766	0.9766	0.9766	128	0.8941	0.9260	0.9098	0.9798
0.0818	17.0	1632	0.0594	0.8495	0.9186	0.8827	86	0.8840	0.8989	0.8914	178	0.9690	0.9766	0.9728	128	0.9032	0.9286	0.9157	0.9814
0.0797	18.0	1728	0.0577	0.8764	0.9070	0.8914	86	0.8840	0.8989	0.8914	178	0.9766	0.9766	0.9766	128	0.9121	0.9260	0.9190	0.9814
0.0745	19.0	1824	0.0573	0.8667	0.9070	0.8864	86	0.8852	0.9101	0.8975	178	0.9766	0.9766	0.9766	128	0.9102	0.9311	0.9206	0.9814
0.0747	20.0	1920	0.0554	0.8478	0.9070	0.8764	86	0.8907	0.9157	0.9030	178	0.9766	0.9766	0.9766	128	0.9082	0.9337	0.9208	0.9816
0.0702	21.0	2016	0.0560	0.8387	0.9070	0.8715	86	0.8876	0.8876	0.8876	178	0.9766	0.9766	0.9766	128	0.9048	0.9209	0.9128	0.9811
0.0701	22.0	2112	0.0550	0.8316	0.9186	0.8729	86	0.8871	0.9270	0.9066	178	0.9766	0.9766	0.9766	128	0.9022	0.9413	0.9213	0.9822
0.0663	23.0	2208	0.0520	0.8478	0.9070	0.8764	86	0.9045	0.9045	0.9045	178	0.9766	0.9766	0.9766	128	0.9146	0.9286	0.9215	0.9833
0.0666	24.0	2304	0.0543	0.8211	0.9070	0.8619	86	0.8870	0.8820	0.8845	178	0.9766	0.9766	0.9766	128	0.9	0.9184	0.9091	0.9806
0.0635	25.0	2400	0.0524	0.8316	0.9186	0.8729	86	0.8927	0.8876	0.8901	178	0.9766	0.9766	0.9766	128	0.905	0.9235	0.9141	0.9822
0.0632	26.0	2496	0.0519	0.8421	0.9302	0.8840	86	0.8927	0.8876	0.8901	178	0.9766	0.9766	0.9766	128	0.9075	0.9260	0.9167	0.9825
0.0596	27.0	2592	0.0489	0.8495	0.9186	0.8827	86	0.8840	0.8989	0.8914	178	0.9766	0.9766	0.9766	128	0.9055	0.9286	0.9169	0.9830
0.0608	28.0	2688	0.0508	0.8316	0.9186	0.8729	86	0.8927	0.8876	0.8901	178	0.9843	0.9766	0.9804	128	0.9073	0.9235	0.9153	0.9825
0.0591	29.0	2784	0.0464	0.8966	0.9070	0.9017	86	0.8962	0.9213	0.9086	178	0.9766	0.9766	0.9766	128	0.9221	0.9362	0.9291	0.9843
0.0582	30.0	2880	0.0472	0.8864	0.9070	0.8966	86	0.9126	0.9382	0.9252	178	0.9766	0.9766	0.9766	128	0.9273	0.9439	0.9355	0.9857
0.0567	31.0	2976	0.0518	0.8333	0.9302	0.8791	86	0.8971	0.8820	0.8895	178	0.9766	0.9766	0.9766	128	0.9073	0.9235	0.9153	0.9825
0.0545	32.0	3072	0.0493	0.8681	0.9186	0.8927	86	0.8956	0.9157	0.9056	178	0.9766	0.9766	0.9766	128	0.9152	0.9362	0.9256	0.9841
0.0526	33.0	3168	0.0488	0.8696	0.9302	0.8989	86	0.8944	0.9045	0.8994	178	0.9688	0.9688	0.9688	128	0.9125	0.9311	0.9217	0.9843
0.0536	34.0	3264	0.0481	0.8989	0.9302	0.9143	86	0.9213	0.9213	0.9213	178	0.9766	0.9766	0.9766	128	0.9342	0.9413	0.9377	0.9843
0.0501	35.0	3360	0.0482	0.8889	0.9302	0.9091	86	0.9157	0.9157	0.9157	178	0.9766	0.9766	0.9766	128	0.9293	0.9388	0.9340	0.9846
0.0541	36.0	3456	0.0481	0.8889	0.9302	0.9091	86	0.9270	0.9270	0.9270	178	0.9766	0.9766	0.9766	128	0.9343	0.9439	0.9391	0.9857
0.0513	37.0	3552	0.0475	0.8778	0.9186	0.8977	86	0.9162	0.9213	0.9188	178	0.9766	0.9766	0.9766	128	0.9270	0.9388	0.9328	0.9857
0.0506	38.0	3648	0.0483	0.8602	0.9302	0.8939	86	0.9045	0.9045	0.9045	178	0.9843	0.9766	0.9804	128	0.9196	0.9337	0.9266	0.9846
0.0483	39.0	3744	0.0498	0.8617	0.9419	0.9000	86	0.9213	0.9213	0.9213	178	0.9843	0.9766	0.9804	128	0.9273	0.9439	0.9355	0.9854
0.0481	40.0	3840	0.0467	0.8876	0.9186	0.9029	86	0.8950	0.9101	0.9025	178	0.9843	0.9766	0.9804	128	0.9219	0.9337	0.9278	0.9846
0.0463	41.0	3936	0.0471	0.8791	0.9302	0.9040	86	0.9050	0.9101	0.9076	178	0.9766	0.9766	0.9766	128	0.9221	0.9362	0.9291	0.9846
0.0461	42.0	4032	0.0456	0.8977	0.9186	0.9080	86	0.9282	0.9438	0.9359	178	0.9764	0.9688	0.9725	128	0.9369	0.9464	0.9416	0.9870
0.0454	43.0	4128	0.0459	0.8791	0.9302	0.9040	86	0.9111	0.9213	0.9162	178	0.9843	0.9766	0.9804	128	0.9271	0.9413	0.9342	0.9860
0.0459	44.0	4224	0.0470	0.8804	0.9419	0.9101	86	0.9282	0.9438	0.9359	178	0.9843	0.9766	0.9804	128	0.935	0.9541	0.9444	0.9873
0.0465	45.0	4320	0.0464	0.8696	0.9302	0.8989	86	0.9322	0.9270	0.9296	178	0.9843	0.9766	0.9804	128	0.9343	0.9439	0.9391	0.9870
0.0468	46.0	4416	0.0483	0.8901	0.9419	0.9153	86	0.9157	0.9157	0.9157	178	0.9764	0.9688	0.9725	128	0.9293	0.9388	0.9340	0.9854
0.0432	47.0	4512	0.0477	0.8901	0.9419	0.9153	86	0.9157	0.9157	0.9157	178	0.9764	0.9688	0.9725	128	0.9293	0.9388	0.9340	0.9857
0.0434	48.0	4608	0.0450	0.8681	0.9186	0.8927	86	0.9270	0.9270	0.9270	178	0.9843	0.9766	0.9804	128	0.9318	0.9413	0.9365	0.9868
0.0442	49.0	4704	0.0464	0.8696	0.9302	0.8989	86	0.9253	0.9045	0.9148	178	0.9766	0.9766	0.9766	128	0.9289	0.9337	0.9313	0.9849
0.0421	50.0	4800	0.0474	0.8696	0.9302	0.8989	86	0.9218	0.9270	0.9244	178	0.9764	0.9688	0.9725	128	0.9271	0.9413	0.9342	0.9865
0.0421	51.0	4896	0.0462	0.8901	0.9419	0.9153	86	0.9106	0.9157	0.9132	178	0.9766	0.9766	0.9766	128	0.9271	0.9413	0.9342	0.9862
0.0415	52.0	4992	0.0461	0.8602	0.9302	0.8939	86	0.9056	0.9157	0.9106	178	0.9843	0.9766	0.9804	128	0.92	0.9388	0.9293	0.9865
0.0418	53.0	5088	0.0455	0.8696	0.9302	0.8989	86	0.9050	0.9101	0.9076	178	0.9766	0.9766	0.9766	128	0.9198	0.9362	0.9279	0.9857
0.0416	54.0	5184	0.0450	0.8696	0.9302	0.8989	86	0.9162	0.9213	0.9188	178	0.9843	0.9766	0.9804	128	0.9271	0.9413	0.9342	0.9865
0.0403	55.0	5280	0.0456	0.8901	0.9419	0.9153	86	0.9153	0.9101	0.9127	178	0.9843	0.9766	0.9804	128	0.9316	0.9388	0.9352	0.9862
0.0424	56.0	5376	0.0458	0.8804	0.9419	0.9101	86	0.9195	0.8989	0.9091	178	0.9766	0.9766	0.9766	128	0.9289	0.9337	0.9313	0.9843
0.0391	57.0	5472	0.0450	0.8901	0.9419	0.9153	86	0.9111	0.9213	0.9162	178	0.9766	0.9766	0.9766	128	0.9273	0.9439	0.9355	0.9868
0.039	58.0	5568	0.0462	0.8901	0.9419	0.9153	86	0.9101	0.9101	0.9101	178	0.9766	0.9766	0.9766	128	0.9270	0.9388	0.9328	0.9857
0.0367	59.0	5664	0.0457	0.8696	0.9302	0.8989	86	0.8939	0.8989	0.8964	178	0.9766	0.9766	0.9766	128	0.9148	0.9311	0.9229	0.9860
0.0396	60.0	5760	0.0450	0.8696	0.9302	0.8989	86	0.9101	0.9101	0.9101	178	0.9766	0.9766	0.9766	128	0.9221	0.9362	0.9291	0.9865
0.038	61.0	5856	0.0451	0.8913	0.9535	0.9213	86	0.9209	0.9157	0.9183	178	0.9843	0.9766	0.9804	128	0.9343	0.9439	0.9391	0.9876
0.0359	62.0	5952	0.0451	0.8913	0.9535	0.9213	86	0.9261	0.9157	0.9209	178	0.9843	0.9766	0.9804	128	0.9367	0.9439	0.9403	0.9870
0.0366	63.0	6048	0.0456	0.9022	0.9651	0.9326	86	0.9213	0.9213	0.9213	178	0.9843	0.9766	0.9804	128	0.9370	0.9490	0.9430	0.9881
0.0346	64.0	6144	0.0452	0.8901	0.9419	0.9153	86	0.9157	0.9157	0.9157	178	0.9843	0.9766	0.9804	128	0.9318	0.9413	0.9365	0.9876
0.0338	65.0	6240	0.0457	0.9022	0.9651	0.9326	86	0.9162	0.9213	0.9188	178	0.9843	0.9766	0.9804	128	0.9347	0.9490	0.9418	0.9881
0.0352	66.0	6336	0.0455	0.8696	0.9302	0.8989	86	0.9101	0.9101	0.9101	178	0.9843	0.9766	0.9804	128	0.9244	0.9362	0.9303	0.9873
0.0351	67.0	6432	0.0456	0.8696	0.9302	0.8989	86	0.9040	0.8989	0.9014	178	0.9843	0.9766	0.9804	128	0.9217	0.9311	0.9264	0.9857
0.0333	68.0	6528	0.0462	0.8817	0.9535	0.9162	86	0.9116	0.9270	0.9192	178	0.9843	0.9766	0.9804	128	0.9277	0.9490	0.9382	0.9881
0.0356	69.0	6624	0.0452	0.8901	0.9419	0.9153	86	0.9091	0.8989	0.9040	178	0.9843	0.9766	0.9804	128	0.9289	0.9337	0.9313	0.9862
0.0336	70.0	6720	0.0455	0.8696	0.9302	0.8989	86	0.9266	0.9213	0.9239	178	0.9843	0.9766	0.9804	128	0.9318	0.9413	0.9365	0.9879
0.0331	71.0	6816	0.0459	0.8710	0.9419	0.9050	86	0.9116	0.9270	0.9192	178	0.9843	0.9766	0.9804	128	0.9252	0.9464	0.9357	0.9876
0.0351	72.0	6912	0.0469	0.8696	0.9302	0.8989	86	0.8989	0.8989	0.8989	178	0.9843	0.9766	0.9804	128	0.9194	0.9311	0.9252	0.9852
0.0333	73.0	7008	0.0466	0.8817	0.9535	0.9162	86	0.9261	0.9157	0.9209	178	0.9764	0.9688	0.9725	128	0.9318	0.9413	0.9365	0.9876
0.0345	74.0	7104	0.0455	0.8817	0.9535	0.9162	86	0.9101	0.9101	0.9101	178	0.9843	0.9766	0.9804	128	0.9271	0.9413	0.9342	0.9873
0.033	75.0	7200	0.0458	0.8710	0.9419	0.9050	86	0.9261	0.9157	0.9209	178	0.9843	0.9766	0.9804	128	0.9318	0.9413	0.9365	0.9879
0.0334	76.0	7296	0.0455	0.8913	0.9535	0.9213	86	0.9205	0.9101	0.9153	178	0.9843	0.9766	0.9804	128	0.9342	0.9413	0.9377	0.9881
0.0332	77.0	7392	0.0442	0.8710	0.9419	0.9050	86	0.9213	0.9213	0.9213	178	0.9843	0.9766	0.9804	128	0.9296	0.9439	0.9367	0.9884
0.0337	78.0	7488	0.0470	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9881
0.0334	79.0	7584	0.0465	0.9022	0.9651	0.9326	86	0.9209	0.9157	0.9183	178	0.9843	0.9766	0.9804	128	0.9369	0.9464	0.9416	0.9873
0.0319	80.0	7680	0.0455	0.9022	0.9651	0.9326	86	0.9318	0.9213	0.9266	178	0.9843	0.9766	0.9804	128	0.9418	0.9490	0.9454	0.9879
0.032	81.0	7776	0.0465	0.9022	0.9651	0.9326	86	0.9318	0.9213	0.9266	178	0.9843	0.9766	0.9804	128	0.9418	0.9490	0.9454	0.9876
0.0328	82.0	7872	0.0450	0.8817	0.9535	0.9162	86	0.9106	0.9157	0.9132	178	0.9843	0.9766	0.9804	128	0.9273	0.9439	0.9355	0.9884
0.032	83.0	7968	0.0449	0.8817	0.9535	0.9162	86	0.9106	0.9157	0.9132	178	0.9843	0.9766	0.9804	128	0.9273	0.9439	0.9355	0.9881
0.0309	84.0	8064	0.0451	0.8817	0.9535	0.9162	86	0.9106	0.9157	0.9132	178	0.9843	0.9766	0.9804	128	0.9273	0.9439	0.9355	0.9879
0.0315	85.0	8160	0.0455	0.8913	0.9535	0.9213	86	0.9205	0.9101	0.9153	178	0.9843	0.9766	0.9804	128	0.9342	0.9413	0.9377	0.9879
0.0305	86.0	8256	0.0456	0.9022	0.9651	0.9326	86	0.9266	0.9213	0.9239	178	0.9843	0.9766	0.9804	128	0.9394	0.9490	0.9442	0.9879
0.0318	87.0	8352	0.0457	0.9022	0.9651	0.9326	86	0.9209	0.9157	0.9183	178	0.9843	0.9766	0.9804	128	0.9369	0.9464	0.9416	0.9873
0.0317	88.0	8448	0.0459	0.9022	0.9651	0.9326	86	0.9209	0.9157	0.9183	178	0.9843	0.9766	0.9804	128	0.9369	0.9464	0.9416	0.9873
0.0319	89.0	8544	0.0463	0.9022	0.9651	0.9326	86	0.9261	0.9157	0.9209	178	0.9843	0.9766	0.9804	128	0.9392	0.9464	0.9428	0.9876
0.0311	90.0	8640	0.0465	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9870
0.0297	91.0	8736	0.0460	0.9022	0.9651	0.9326	86	0.9257	0.9101	0.9178	178	0.9843	0.9766	0.9804	128	0.9391	0.9439	0.9415	0.9876
0.0306	92.0	8832	0.0462	0.9022	0.9651	0.9326	86	0.9257	0.9101	0.9178	178	0.9843	0.9766	0.9804	128	0.9391	0.9439	0.9415	0.9876
0.0335	93.0	8928	0.0460	0.8913	0.9535	0.9213	86	0.92	0.9045	0.9122	178	0.9843	0.9766	0.9804	128	0.9340	0.9388	0.9364	0.9870
0.0288	94.0	9024	0.0462	0.9022	0.9651	0.9326	86	0.9318	0.9213	0.9266	178	0.9843	0.9766	0.9804	128	0.9418	0.9490	0.9454	0.9881
0.0296	95.0	9120	0.0459	0.9022	0.9651	0.9326	86	0.9368	0.9157	0.9261	178	0.9843	0.9766	0.9804	128	0.9440	0.9464	0.9452	0.9881
0.0317	96.0	9216	0.0455	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9884
0.0298	97.0	9312	0.0457	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9884
0.0295	98.0	9408	0.0456	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9884
0.0303	99.0	9504	0.0458	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9884
0.0304	100.0	9600	0.0458	0.9022	0.9651	0.9326	86	0.9314	0.9157	0.9235	178	0.9843	0.9766	0.9804	128	0.9416	0.9464	0.9440	0.9884

Framework versions

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