nerui-lora-r16-0

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:

• Loss: 0.0440
• Location Precision: 0.8318
• Location Recall: 0.9468
• Location F1: 0.8856
• Location Number: 94
• Organization Precision: 0.8827
• Organization Recall: 0.8563
• Organization F1: 0.8693
• Organization Number: 167
• Person Precision: 1.0
• Person Recall: 0.9854
• Person F1: 0.9926
• Person Number: 137
• Overall Precision: 0.9084
• Overall Recall: 0.9221
• Overall F1: 0.9152
• Overall Accuracy: 0.9845

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
1.0607	1.0	96	0.6834	0.0	0.0	0.0	94	0.0	0.0	0.0	167	0.0	0.0	0.0	137	0.0	0.0	0.0	0.8343
0.6397	2.0	192	0.5323	0.0	0.0	0.0	94	0.6667	0.0240	0.0462	167	0.2	0.0146	0.0272	137	0.375	0.0151	0.0290	0.8367
0.4975	3.0	288	0.3811	0.16	0.0426	0.0672	94	0.2903	0.1617	0.2077	167	0.2606	0.2701	0.2652	137	0.2615	0.1709	0.2067	0.8663
0.3542	4.0	384	0.2727	0.3231	0.2234	0.2642	94	0.4834	0.6108	0.5397	167	0.4343	0.6277	0.5134	137	0.4409	0.5251	0.4794	0.9141
0.2514	5.0	480	0.1973	0.5393	0.5106	0.5246	94	0.6049	0.7425	0.6667	167	0.7532	0.8686	0.8068	137	0.6438	0.7312	0.6847	0.9434
0.2019	6.0	576	0.1491	0.6915	0.6915	0.6915	94	0.7228	0.7964	0.7578	167	0.9161	0.9562	0.9357	137	0.7815	0.8266	0.8034	0.9602
0.1643	7.0	672	0.1244	0.7170	0.8085	0.76	94	0.7308	0.7964	0.7622	167	0.9301	0.9708	0.9500	137	0.7935	0.8593	0.8251	0.9644
0.1449	8.0	768	0.1025	0.7475	0.7872	0.7668	94	0.7697	0.8204	0.7942	167	0.9496	0.9635	0.9565	137	0.8245	0.8618	0.8428	0.9693
0.1318	9.0	864	0.0919	0.8163	0.8511	0.8333	94	0.7838	0.8683	0.8239	167	0.95	0.9708	0.9603	137	0.8463	0.8995	0.8721	0.9721
0.1184	10.0	960	0.0846	0.8	0.8936	0.8442	94	0.8246	0.8443	0.8343	167	0.9504	0.9781	0.9640	137	0.8609	0.9020	0.8810	0.9751
0.11	11.0	1056	0.0744	0.8454	0.8723	0.8586	94	0.8324	0.8623	0.8471	167	0.9571	0.9781	0.9675	137	0.8780	0.9045	0.8911	0.9773
0.103	12.0	1152	0.0714	0.8431	0.9149	0.8776	94	0.8471	0.8623	0.8546	167	0.9571	0.9781	0.9675	137	0.8835	0.9146	0.8988	0.9776
0.0954	13.0	1248	0.0672	0.8586	0.9043	0.8808	94	0.8471	0.8623	0.8546	167	0.9853	0.9781	0.9817	137	0.8963	0.9121	0.9041	0.9790
0.0896	14.0	1344	0.0617	0.8673	0.9043	0.8854	94	0.8466	0.8922	0.8688	167	0.9710	0.9781	0.9745	137	0.8932	0.9246	0.9086	0.9804
0.0894	15.0	1440	0.0573	0.8687	0.9149	0.8912	94	0.8596	0.8802	0.8698	167	0.9640	0.9781	0.9710	137	0.8973	0.9221	0.9095	0.9801
0.0853	16.0	1536	0.0628	0.8462	0.9362	0.8889	94	0.8457	0.8862	0.8655	167	0.9783	0.9854	0.9818	137	0.8897	0.9322	0.9104	0.9798
0.0813	17.0	1632	0.0562	0.8763	0.9043	0.8901	94	0.8629	0.9042	0.8830	167	0.9640	0.9781	0.9710	137	0.9002	0.9296	0.9147	0.9815
0.0804	18.0	1728	0.0545	0.85	0.9043	0.8763	94	0.8529	0.8683	0.8605	167	0.9571	0.9781	0.9675	137	0.8878	0.9146	0.9010	0.9798
0.0761	19.0	1824	0.0517	0.84	0.8936	0.8660	94	0.8675	0.8623	0.8649	167	0.9853	0.9781	0.9817	137	0.9005	0.9095	0.905	0.9812
0.0761	20.0	1920	0.0532	0.84	0.8936	0.8660	94	0.8706	0.8862	0.8783	167	0.9781	0.9781	0.9781	137	0.8993	0.9196	0.9093	0.9815
0.071	21.0	2016	0.0553	0.8462	0.9362	0.8889	94	0.8659	0.8503	0.8580	167	0.9781	0.9781	0.9781	137	0.8988	0.9146	0.9066	0.9812
0.07	22.0	2112	0.0499	0.85	0.9043	0.8763	94	0.8728	0.9042	0.8882	167	0.9926	0.9854	0.9890	137	0.9071	0.9322	0.9195	0.9834
0.0673	23.0	2208	0.0517	0.8286	0.9255	0.8744	94	0.8712	0.8503	0.8606	167	0.9783	0.9854	0.9818	137	0.8966	0.9146	0.9055	0.9820
0.0657	24.0	2304	0.0489	0.8515	0.9149	0.8821	94	0.8772	0.8982	0.8876	167	0.9853	0.9781	0.9817	137	0.9069	0.9296	0.9181	0.9831
0.0643	25.0	2400	0.0501	0.8148	0.9362	0.8713	94	0.8805	0.8383	0.8589	167	1.0	0.9854	0.9926	137	0.9030	0.9121	0.9075	0.9823
0.0607	26.0	2496	0.0486	0.8317	0.8936	0.8615	94	0.8841	0.8683	0.8761	167	1.0	0.9854	0.9926	137	0.91	0.9146	0.9123	0.9837
0.0629	27.0	2592	0.0493	0.8571	0.8936	0.875	94	0.8802	0.8802	0.8802	167	0.9779	0.9708	0.9744	137	0.9077	0.9146	0.9111	0.9826
0.0571	28.0	2688	0.0495	0.85	0.9043	0.8763	94	0.8727	0.8623	0.8675	167	0.9926	0.9781	0.9853	137	0.9075	0.9121	0.9098	0.9823
0.0564	29.0	2784	0.0469	0.8544	0.9362	0.8934	94	0.8909	0.8802	0.8855	167	0.9926	0.9781	0.9853	137	0.9156	0.9271	0.9213	0.9851
0.0578	30.0	2880	0.0486	0.8476	0.9468	0.8945	94	0.875	0.8802	0.8776	167	0.9853	0.9781	0.9817	137	0.9046	0.9296	0.9170	0.9837
0.0571	31.0	2976	0.0466	0.87	0.9255	0.8969	94	0.8727	0.8623	0.8675	167	0.9926	0.9781	0.9853	137	0.9125	0.9171	0.9148	0.9848
0.0517	32.0	3072	0.0480	0.8091	0.9468	0.8725	94	0.8704	0.8443	0.8571	167	1.0	0.9854	0.9926	137	0.8968	0.9171	0.9068	0.9829
0.0509	33.0	3168	0.0467	0.8224	0.9362	0.8756	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9015	0.9196	0.9104	0.9837
0.051	34.0	3264	0.0469	0.8286	0.9255	0.8744	94	0.8780	0.8623	0.8701	167	0.9926	0.9781	0.9853	137	0.9035	0.9171	0.9102	0.9834
0.0509	35.0	3360	0.0447	0.85	0.9043	0.8763	94	0.8848	0.8743	0.8795	167	1.0	0.9854	0.9926	137	0.915	0.9196	0.9173	0.9845
0.0498	36.0	3456	0.0467	0.8614	0.9255	0.8923	94	0.8713	0.8922	0.8817	167	0.9926	0.9781	0.9853	137	0.9091	0.9296	0.9193	0.9843
0.0486	37.0	3552	0.0439	0.86	0.9149	0.8866	94	0.8862	0.8862	0.8862	167	0.9926	0.9781	0.9853	137	0.9154	0.9246	0.92	0.9845
0.0486	38.0	3648	0.0430	0.8529	0.9255	0.8878	94	0.8896	0.8683	0.8788	167	0.9926	0.9781	0.9853	137	0.915	0.9196	0.9173	0.9845
0.0508	39.0	3744	0.0458	0.8224	0.9362	0.8756	94	0.8758	0.8443	0.8598	167	0.9926	0.9781	0.9853	137	0.9007	0.9121	0.9064	0.9837
0.0487	40.0	3840	0.0416	0.8544	0.9362	0.8934	94	0.8869	0.8922	0.8896	167	1.0	0.9854	0.9926	137	0.9163	0.9347	0.9254	0.9859
0.0453	41.0	3936	0.0431	0.8302	0.9362	0.88	94	0.8889	0.8623	0.8754	167	1.0	0.9854	0.9926	137	0.9107	0.9221	0.9164	0.9848
0.0459	42.0	4032	0.0421	0.8673	0.9043	0.8854	94	0.8909	0.8802	0.8855	167	1.0	0.9854	0.9926	137	0.9221	0.9221	0.9221	0.9854
0.0461	43.0	4128	0.0444	0.8286	0.9255	0.8744	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9057	0.9171	0.9114	0.9840
0.0436	44.0	4224	0.0418	0.8515	0.9149	0.8821	94	0.8712	0.8503	0.8606	167	1.0	0.9854	0.9926	137	0.9098	0.9121	0.9109	0.9837
0.0444	45.0	4320	0.0397	0.8614	0.9255	0.8923	94	0.8970	0.8862	0.8916	167	1.0	0.9854	0.9926	137	0.9227	0.9296	0.9262	0.9867
0.042	46.0	4416	0.0421	0.8286	0.9255	0.8744	94	0.8820	0.8503	0.8659	167	1.0	0.9854	0.9926	137	0.9077	0.9146	0.9111	0.9848
0.0425	47.0	4512	0.0443	0.8241	0.9468	0.8812	94	0.8841	0.8683	0.8761	167	1.0	0.9854	0.9926	137	0.9066	0.9271	0.9168	0.9845
0.0416	48.0	4608	0.0418	0.8462	0.9362	0.8889	94	0.9012	0.8743	0.8875	167	1.0	0.9854	0.9926	137	0.9202	0.9271	0.9237	0.9862
0.0401	49.0	4704	0.0418	0.8544	0.9362	0.8934	94	0.8841	0.8683	0.8761	167	1.0	0.9854	0.9926	137	0.9154	0.9246	0.92	0.9854
0.0395	50.0	4800	0.0428	0.8365	0.9255	0.8788	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9080	0.9171	0.9125	0.9848
0.0404	51.0	4896	0.0426	0.8462	0.9362	0.8889	94	0.8712	0.8503	0.8606	167	1.0	0.9854	0.9926	137	0.9080	0.9171	0.9125	0.9848
0.0388	52.0	4992	0.0405	0.8889	0.9362	0.9119	94	0.8824	0.8982	0.8902	167	1.0	0.9854	0.9926	137	0.9233	0.9372	0.9302	0.9876
0.0406	53.0	5088	0.0409	0.87	0.9255	0.8969	94	0.875	0.8802	0.8776	167	1.0	0.9854	0.9926	137	0.9156	0.9271	0.9213	0.9856
0.0403	54.0	5184	0.0410	0.8713	0.9362	0.9026	94	0.8855	0.8802	0.8829	167	1.0	0.9854	0.9926	137	0.9204	0.9296	0.925	0.9856
0.0393	55.0	5280	0.0407	0.8529	0.9255	0.8878	94	0.8580	0.8683	0.8631	167	1.0	0.9854	0.9926	137	0.9039	0.9221	0.9129	0.9854
0.0397	56.0	5376	0.0408	0.8302	0.9362	0.88	94	0.8598	0.8443	0.8520	167	1.0	0.9854	0.9926	137	0.8988	0.9146	0.9066	0.9834
0.0376	57.0	5472	0.0423	0.8257	0.9574	0.8867	94	0.8812	0.8443	0.8624	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9845
0.0385	58.0	5568	0.0406	0.8687	0.9149	0.8912	94	0.8743	0.8743	0.8743	167	1.0	0.9854	0.9926	137	0.9152	0.9221	0.9186	0.9856
0.0371	59.0	5664	0.0407	0.8776	0.9149	0.8958	94	0.8855	0.8802	0.8829	167	1.0	0.9854	0.9926	137	0.9223	0.9246	0.9235	0.9865
0.0361	60.0	5760	0.0428	0.8318	0.9468	0.8856	94	0.9062	0.8683	0.8869	167	1.0	0.9854	0.9926	137	0.9179	0.9271	0.9225	0.9851
0.036	61.0	5856	0.0413	0.8713	0.9362	0.9026	94	0.8935	0.9042	0.8988	167	1.0	0.9854	0.9926	137	0.9235	0.9397	0.9315	0.9862
0.0383	62.0	5952	0.0421	0.8302	0.9362	0.88	94	0.8909	0.8802	0.8855	167	1.0	0.9854	0.9926	137	0.9113	0.9296	0.9204	0.9848
0.0339	63.0	6048	0.0419	0.8381	0.9362	0.8844	94	0.9012	0.8743	0.8875	167	1.0	0.9854	0.9926	137	0.9179	0.9271	0.9225	0.9854
0.0363	64.0	6144	0.0428	0.8241	0.9468	0.8812	94	0.875	0.8383	0.8563	167	1.0	0.9854	0.9926	137	0.9032	0.9146	0.9089	0.9845
0.0355	65.0	6240	0.0422	0.8224	0.9362	0.8756	94	0.8650	0.8443	0.8545	167	1.0	0.9854	0.9926	137	0.8988	0.9146	0.9066	0.9845
0.0339	66.0	6336	0.0448	0.8241	0.9468	0.8812	94	0.8831	0.8144	0.8474	167	1.0	0.9854	0.9926	137	0.9068	0.9045	0.9057	0.9829
0.0352	67.0	6432	0.0429	0.8318	0.9468	0.8856	94	0.8820	0.8503	0.8659	167	1.0	0.9854	0.9926	137	0.9082	0.9196	0.9139	0.9843
0.0337	68.0	6528	0.0458	0.8241	0.9468	0.8812	94	0.8710	0.8084	0.8385	167	1.0	0.9854	0.9926	137	0.9020	0.9020	0.9020	0.9826
0.0353	69.0	6624	0.0425	0.8381	0.9362	0.8844	94	0.8841	0.8683	0.8761	167	1.0	0.9854	0.9926	137	0.9109	0.9246	0.9177	0.9851
0.0338	70.0	6720	0.0428	0.8365	0.9255	0.8788	94	0.8589	0.8383	0.8485	167	1.0	0.9854	0.9926	137	0.9005	0.9095	0.905	0.9834
0.0348	71.0	6816	0.0432	0.8318	0.9468	0.8856	94	0.9012	0.8743	0.8875	167	0.9926	0.9781	0.9853	137	0.9134	0.9271	0.9202	0.9851
0.0351	72.0	6912	0.0449	0.8091	0.9468	0.8725	94	0.8868	0.8443	0.8650	167	1.0	0.9854	0.9926	137	0.9035	0.9171	0.9102	0.9837
0.0327	73.0	7008	0.0439	0.8091	0.9468	0.8725	94	0.8625	0.8263	0.8440	167	1.0	0.9854	0.9926	137	0.8938	0.9095	0.9016	0.9826
0.0314	74.0	7104	0.0431	0.8462	0.9362	0.8889	94	0.8758	0.8443	0.8598	167	1.0	0.9854	0.9926	137	0.91	0.9146	0.9123	0.9837
0.0332	75.0	7200	0.0430	0.8302	0.9362	0.88	94	0.8485	0.8383	0.8434	167	1.0	0.9854	0.9926	137	0.8941	0.9121	0.9030	0.9834
0.0311	76.0	7296	0.0438	0.8365	0.9255	0.8788	94	0.8598	0.8443	0.8520	167	1.0	0.9854	0.9926	137	0.9007	0.9121	0.9064	0.9840
0.0322	77.0	7392	0.0455	0.8165	0.9468	0.8768	94	0.8671	0.8204	0.8431	167	1.0	0.9854	0.9926	137	0.8980	0.9070	0.9025	0.9823
0.0313	78.0	7488	0.0442	0.8302	0.9362	0.88	94	0.8712	0.8503	0.8606	167	1.0	0.9854	0.9926	137	0.9035	0.9171	0.9102	0.9840
0.0313	79.0	7584	0.0435	0.8302	0.9362	0.88	94	0.8659	0.8503	0.8580	167	1.0	0.9854	0.9926	137	0.9012	0.9171	0.9091	0.9845
0.0321	80.0	7680	0.0450	0.8165	0.9468	0.8768	94	0.8812	0.8443	0.8624	167	1.0	0.9854	0.9926	137	0.9035	0.9171	0.9102	0.9831
0.0303	81.0	7776	0.0441	0.8318	0.9468	0.8856	94	0.8765	0.8503	0.8632	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9843
0.0322	82.0	7872	0.0442	0.8318	0.9468	0.8856	94	0.8797	0.8323	0.8554	167	1.0	0.9854	0.9926	137	0.9075	0.9121	0.9098	0.9834
0.0313	83.0	7968	0.0447	0.8318	0.9468	0.8856	94	0.8812	0.8443	0.8624	167	1.0	0.9854	0.9926	137	0.9080	0.9171	0.9125	0.9834
0.0292	84.0	8064	0.0448	0.8318	0.9468	0.8856	94	0.8765	0.8503	0.8632	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9840
0.03	85.0	8160	0.0465	0.8396	0.9468	0.89	94	0.8734	0.8263	0.8492	167	1.0	0.9854	0.9926	137	0.9073	0.9095	0.9084	0.9831
0.0311	86.0	8256	0.0455	0.8302	0.9362	0.88	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9837
0.0302	87.0	8352	0.0458	0.8318	0.9468	0.8856	94	0.8696	0.8383	0.8537	167	1.0	0.9854	0.9926	137	0.9032	0.9146	0.9089	0.9834
0.0311	88.0	8448	0.0445	0.8318	0.9468	0.8856	94	0.8758	0.8443	0.8598	167	1.0	0.9854	0.9926	137	0.9057	0.9171	0.9114	0.9834
0.0306	89.0	8544	0.0432	0.8365	0.9255	0.8788	94	0.8727	0.8623	0.8675	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9843
0.0292	90.0	8640	0.0444	0.8396	0.9468	0.89	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9107	0.9221	0.9164	0.9837
0.0302	91.0	8736	0.0451	0.8318	0.9468	0.8856	94	0.875	0.8383	0.8563	167	1.0	0.9854	0.9926	137	0.9055	0.9146	0.91	0.9829
0.0288	92.0	8832	0.0445	0.8396	0.9468	0.89	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9845
0.0313	93.0	8928	0.0444	0.8318	0.9468	0.8856	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9845
0.0293	94.0	9024	0.0441	0.8318	0.9468	0.8856	94	0.8944	0.8623	0.8780	167	1.0	0.9854	0.9926	137	0.9132	0.9246	0.9189	0.9848
0.03	95.0	9120	0.0450	0.8318	0.9468	0.8856	94	0.8812	0.8443	0.8624	167	1.0	0.9854	0.9926	137	0.9080	0.9171	0.9125	0.9837
0.0313	96.0	9216	0.0443	0.8318	0.9468	0.8856	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9845
0.0299	97.0	9312	0.0445	0.8318	0.9468	0.8856	94	0.875	0.8383	0.8563	167	1.0	0.9854	0.9926	137	0.9055	0.9146	0.91	0.9837
0.0316	98.0	9408	0.0442	0.8318	0.9468	0.8856	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9845
0.0301	99.0	9504	0.0439	0.8318	0.9468	0.8856	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9845
0.0308	100.0	9600	0.0440	0.8318	0.9468	0.8856	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9845

Framework versions

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