nerui-lora-r8-0

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: 0.0463
• Location Precision: 0.8462
• Location Recall: 0.9362
• Location F1: 0.8889
• Location Number: 94
• Organization Precision: 0.8667
• Organization Recall: 0.8563
• Organization F1: 0.8614
• Organization Number: 167
• Person Precision: 1.0
• Person Recall: 0.9854
• Person F1: 0.9926
• Person Number: 137
• Overall Precision: 0.9059
• Overall Recall: 0.9196
• Overall F1: 0.9127
• Overall Accuracy: 0.9848

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
1.1434	1.0	96	0.7069	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
0.6699	2.0	192	0.5760	0.0	0.0	0.0	94	1.0	0.0060	0.0119	167	0.0	0.0	0.0	137	0.25	0.0025	0.0050	0.8348
0.5654	3.0	288	0.4641	0.0	0.0	0.0	94	0.4118	0.0419	0.0761	167	0.2414	0.0511	0.0843	137	0.3043	0.0352	0.0631	0.8420
0.4481	4.0	384	0.3466	0.2353	0.0426	0.0721	94	0.3578	0.2335	0.2826	167	0.3774	0.4380	0.4054	137	0.3614	0.2588	0.3016	0.8793
0.3376	5.0	480	0.2613	0.4058	0.2979	0.3436	94	0.5105	0.5808	0.5434	167	0.5081	0.6861	0.5839	137	0.4932	0.5503	0.5202	0.9202
0.2611	6.0	576	0.2025	0.5909	0.5532	0.5714	94	0.5588	0.6826	0.6146	167	0.6905	0.8467	0.7607	137	0.6130	0.7085	0.6573	0.9406
0.2071	7.0	672	0.1615	0.7021	0.7021	0.7021	94	0.6649	0.7605	0.7095	167	0.8224	0.9124	0.8651	137	0.7277	0.7990	0.7617	0.9555
0.1767	8.0	768	0.1337	0.7872	0.7872	0.7872	94	0.7120	0.7844	0.7464	167	0.9306	0.9781	0.9537	137	0.8033	0.8518	0.8268	0.9644
0.1601	9.0	864	0.1165	0.7980	0.8404	0.8187	94	0.7351	0.8144	0.7727	167	0.9306	0.9781	0.9537	137	0.8154	0.8769	0.8450	0.9671
0.1406	10.0	960	0.1041	0.7573	0.8298	0.7919	94	0.7816	0.8144	0.7977	167	0.9371	0.9781	0.9571	137	0.8286	0.8744	0.8509	0.9693
0.1283	11.0	1056	0.0951	0.8021	0.8191	0.8105	94	0.7865	0.8383	0.8116	167	0.9371	0.9781	0.9571	137	0.8417	0.8819	0.8613	0.9704
0.1229	12.0	1152	0.0895	0.8019	0.9043	0.8500	94	0.8	0.8383	0.8187	167	0.9375	0.9854	0.9609	137	0.8471	0.9045	0.8748	0.9715
0.1116	13.0	1248	0.0831	0.83	0.8830	0.8557	94	0.8314	0.8563	0.8437	167	0.9371	0.9781	0.9571	137	0.8675	0.9045	0.8856	0.9743
0.1077	14.0	1344	0.0769	0.8571	0.8936	0.875	94	0.8409	0.8862	0.8630	167	0.9504	0.9781	0.9640	137	0.8819	0.9196	0.9004	0.9760
0.1045	15.0	1440	0.0758	0.8333	0.9043	0.8673	94	0.8430	0.8683	0.8555	167	0.9371	0.9781	0.9571	137	0.8729	0.9146	0.8933	0.9760
0.1	16.0	1536	0.0753	0.8365	0.9255	0.8788	94	0.8111	0.8743	0.8415	167	0.9437	0.9781	0.9606	137	0.8615	0.9221	0.8908	0.9746
0.0961	17.0	1632	0.0690	0.8586	0.9043	0.8808	94	0.8563	0.8922	0.8739	167	0.9571	0.9781	0.9675	137	0.8910	0.9246	0.9075	0.9785
0.0981	18.0	1728	0.0676	0.86	0.9149	0.8866	94	0.8523	0.8982	0.8746	167	0.9504	0.9781	0.9640	137	0.8873	0.9296	0.9080	0.9782
0.0916	19.0	1824	0.0653	0.8333	0.9043	0.8673	94	0.8647	0.8802	0.8724	167	0.9640	0.9781	0.9710	137	0.8905	0.9196	0.9048	0.9790
0.0899	20.0	1920	0.0637	0.8586	0.9043	0.8808	94	0.8563	0.8922	0.8739	167	0.9640	0.9781	0.9710	137	0.8932	0.9246	0.9086	0.9790
0.0856	21.0	2016	0.0656	0.8113	0.9149	0.8600	94	0.8580	0.8683	0.8631	167	0.9571	0.9781	0.9675	137	0.8795	0.9171	0.8979	0.9773
0.0844	22.0	2112	0.0621	0.8416	0.9043	0.8718	94	0.8563	0.8922	0.8739	167	0.9571	0.9781	0.9675	137	0.8867	0.9246	0.9053	0.9782
0.0816	23.0	2208	0.0608	0.85	0.9043	0.8763	94	0.8647	0.8802	0.8724	167	0.9571	0.9781	0.9675	137	0.8927	0.9196	0.9059	0.9798
0.0803	24.0	2304	0.0591	0.8586	0.9043	0.8808	94	0.8671	0.8982	0.8824	167	0.9571	0.9781	0.9675	137	0.8956	0.9271	0.9111	0.9796
0.0793	25.0	2400	0.0577	0.85	0.9043	0.8763	94	0.8824	0.8982	0.8902	167	0.9710	0.9781	0.9745	137	0.9044	0.9271	0.9156	0.9818
0.0744	26.0	2496	0.0576	0.8529	0.9255	0.8878	94	0.8706	0.8862	0.8783	167	0.9710	0.9781	0.9745	137	0.9	0.9271	0.9134	0.9818
0.0761	27.0	2592	0.0571	0.8416	0.9043	0.8718	94	0.8757	0.8862	0.8810	167	0.9640	0.9781	0.9710	137	0.8973	0.9221	0.9095	0.9807
0.0724	28.0	2688	0.0559	0.8586	0.9043	0.8808	94	0.8655	0.8862	0.8757	167	0.9710	0.9781	0.9745	137	0.8995	0.9221	0.9107	0.9809
0.071	29.0	2784	0.0542	0.8687	0.9149	0.8912	94	0.8655	0.8862	0.8757	167	0.9783	0.9854	0.9818	137	0.9044	0.9271	0.9156	0.9818
0.0705	30.0	2880	0.0549	0.8462	0.9362	0.8889	94	0.8690	0.8743	0.8716	167	0.9854	0.9854	0.9854	137	0.9022	0.9271	0.9145	0.9818
0.0702	31.0	2976	0.0517	0.8687	0.9149	0.8912	94	0.8817	0.8922	0.8869	167	1.0	0.9854	0.9926	137	0.9181	0.9296	0.9238	0.9834
0.065	32.0	3072	0.0532	0.8396	0.9468	0.89	94	0.8951	0.8683	0.8815	167	0.9926	0.9854	0.9890	137	0.9134	0.9271	0.9202	0.9826
0.0639	33.0	3168	0.0533	0.8286	0.9255	0.8744	94	0.8780	0.8623	0.8701	167	0.9926	0.9854	0.9890	137	0.9037	0.9196	0.9116	0.9815
0.0642	34.0	3264	0.0520	0.8529	0.9255	0.8878	94	0.875	0.8802	0.8776	167	0.9926	0.9854	0.9890	137	0.9089	0.9271	0.9179	0.9820
0.0652	35.0	3360	0.0518	0.8515	0.9149	0.8821	94	0.8690	0.8743	0.8716	167	0.9926	0.9854	0.9890	137	0.9062	0.9221	0.9141	0.9815
0.0627	36.0	3456	0.0533	0.87	0.9255	0.8969	94	0.8655	0.8862	0.8757	167	0.9854	0.9854	0.9854	137	0.9069	0.9296	0.9181	0.9818
0.0606	37.0	3552	0.0503	0.8878	0.9255	0.9062	94	0.8698	0.8802	0.8750	167	0.9926	0.9854	0.9890	137	0.9156	0.9271	0.9213	0.9826
0.0611	38.0	3648	0.0497	0.87	0.9255	0.8969	94	0.8848	0.8743	0.8795	167	0.9854	0.9854	0.9854	137	0.9154	0.9246	0.92	0.9829
0.0645	39.0	3744	0.0511	0.8431	0.9149	0.8776	94	0.8780	0.8623	0.8701	167	0.9926	0.9854	0.9890	137	0.9080	0.9171	0.9125	0.9823
0.061	40.0	3840	0.0487	0.8687	0.9149	0.8912	94	0.8765	0.8922	0.8843	167	1.0	0.9854	0.9926	137	0.9158	0.9296	0.9227	0.9840
0.0591	41.0	3936	0.0491	0.8515	0.9149	0.8821	94	0.8802	0.8802	0.8802	167	1.0	0.9854	0.9926	137	0.9132	0.9246	0.9189	0.9834
0.058	42.0	4032	0.0480	0.8687	0.9149	0.8912	94	0.8757	0.8862	0.8810	167	1.0	0.9854	0.9926	137	0.9156	0.9271	0.9213	0.9840
0.0587	43.0	4128	0.0494	0.8350	0.9149	0.8731	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9055	0.9146	0.91	0.9820
0.0562	44.0	4224	0.0482	0.8515	0.9149	0.8821	94	0.8788	0.8683	0.8735	167	1.0	0.9854	0.9926	137	0.9127	0.9196	0.9161	0.9829
0.0565	45.0	4320	0.0471	0.8529	0.9255	0.8878	94	0.8795	0.8743	0.8769	167	1.0	0.9854	0.9926	137	0.9132	0.9246	0.9189	0.9837
0.0541	46.0	4416	0.0482	0.8365	0.9255	0.8788	94	0.8795	0.8743	0.8769	167	1.0	0.9854	0.9926	137	0.9086	0.9246	0.9166	0.9831
0.0547	47.0	4512	0.0487	0.8350	0.9149	0.8731	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9055	0.9146	0.91	0.9823
0.0537	48.0	4608	0.0480	0.8269	0.9149	0.8687	94	0.8659	0.8503	0.8580	167	1.0	0.9854	0.9926	137	0.9007	0.9121	0.9064	0.9829
0.0525	49.0	4704	0.0477	0.8416	0.9043	0.8718	94	0.8882	0.8563	0.8720	167	1.0	0.9854	0.9926	137	0.9144	0.9121	0.9132	0.9826
0.0513	50.0	4800	0.0472	0.86	0.9149	0.8866	94	0.8596	0.8802	0.8698	167	1.0	0.9854	0.9926	137	0.9064	0.9246	0.9154	0.9845
0.0507	51.0	4896	0.0481	0.8286	0.9255	0.8744	94	0.875	0.8383	0.8563	167	1.0	0.9854	0.9926	137	0.905	0.9095	0.9073	0.9820
0.0499	52.0	4992	0.0472	0.87	0.9255	0.8969	94	0.8757	0.8862	0.8810	167	1.0	0.9854	0.9926	137	0.9158	0.9296	0.9227	0.9837
0.0519	53.0	5088	0.0471	0.8614	0.9255	0.8923	94	0.8743	0.8743	0.8743	167	1.0	0.9854	0.9926	137	0.9132	0.9246	0.9189	0.9840
0.0523	54.0	5184	0.0483	0.8286	0.9255	0.8744	94	0.8545	0.8443	0.8494	167	1.0	0.9854	0.9926	137	0.8963	0.9121	0.9041	0.9826
0.0507	55.0	5280	0.0465	0.8447	0.9255	0.8832	94	0.8614	0.8563	0.8589	167	1.0	0.9854	0.9926	137	0.9035	0.9171	0.9102	0.9831
0.0506	56.0	5376	0.0465	0.8447	0.9255	0.8832	94	0.8614	0.8563	0.8589	167	1.0	0.9854	0.9926	137	0.9035	0.9171	0.9102	0.9831
0.0504	57.0	5472	0.0475	0.8208	0.9255	0.8700	94	0.8452	0.8503	0.8478	167	1.0	0.9854	0.9926	137	0.8900	0.9146	0.9021	0.9831
0.0484	58.0	5568	0.0462	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	0.9837
0.0487	59.0	5664	0.0457	0.8447	0.9255	0.8832	94	0.8727	0.8623	0.8675	167	1.0	0.9854	0.9926	137	0.9082	0.9196	0.9139	0.9837
0.0463	60.0	5760	0.0475	0.8365	0.9255	0.8788	94	0.8623	0.8623	0.8623	167	1.0	0.9854	0.9926	137	0.9015	0.9196	0.9104	0.9848
0.0462	61.0	5856	0.0469	0.8529	0.9255	0.8878	94	0.8655	0.8862	0.8757	167	1.0	0.9854	0.9926	137	0.9069	0.9296	0.9181	0.9848
0.0497	62.0	5952	0.0469	0.8544	0.9362	0.8934	94	0.8521	0.8623	0.8571	167	1.0	0.9854	0.9926	137	0.9017	0.9221	0.9118	0.9845
0.0465	63.0	6048	0.0469	0.8515	0.9149	0.8821	94	0.8683	0.8683	0.8683	167	1.0	0.9854	0.9926	137	0.9082	0.9196	0.9139	0.9848
0.0468	64.0	6144	0.0470	0.86	0.9149	0.8866	94	0.8841	0.8683	0.8761	167	1.0	0.9854	0.9926	137	0.9173	0.9196	0.9184	0.9843
0.0455	65.0	6240	0.0467	0.8462	0.9362	0.8889	94	0.8675	0.8623	0.8649	167	1.0	0.9854	0.9926	137	0.9062	0.9221	0.9141	0.9845
0.0456	66.0	6336	0.0463	0.8431	0.9149	0.8776	94	0.8712	0.8503	0.8606	167	1.0	0.9854	0.9926	137	0.9075	0.9121	0.9098	0.9834
0.0436	67.0	6432	0.0457	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	0.9837
0.0442	68.0	6528	0.0464	0.8365	0.9255	0.8788	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9057	0.9171	0.9114	0.9837
0.0463	69.0	6624	0.0463	0.8447	0.9255	0.8832	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9080	0.9171	0.9125	0.9840
0.0445	70.0	6720	0.0457	0.8529	0.9255	0.8878	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9102	0.9171	0.9136	0.9840
0.0456	71.0	6816	0.0474	0.8462	0.9362	0.8889	94	0.8788	0.8683	0.8735	167	1.0	0.9854	0.9926	137	0.9109	0.9246	0.9177	0.9851
0.0473	72.0	6912	0.0479	0.8381	0.9362	0.8844	94	0.8659	0.8503	0.8580	167	1.0	0.9854	0.9926	137	0.9035	0.9171	0.9102	0.9837
0.0434	73.0	7008	0.0475	0.8381	0.9362	0.8844	94	0.8712	0.8503	0.8606	167	1.0	0.9854	0.9926	137	0.9057	0.9171	0.9114	0.9840
0.042	74.0	7104	0.0463	0.8462	0.9362	0.8889	94	0.8765	0.8503	0.8632	167	1.0	0.9854	0.9926	137	0.9102	0.9171	0.9136	0.9837
0.0438	75.0	7200	0.0463	0.8462	0.9362	0.8889	94	0.8765	0.8503	0.8632	167	1.0	0.9854	0.9926	137	0.9102	0.9171	0.9136	0.9837
0.0437	76.0	7296	0.0459	0.8462	0.9362	0.8889	94	0.8623	0.8623	0.8623	167	1.0	0.9854	0.9926	137	0.9039	0.9221	0.9129	0.9843
0.0455	77.0	7392	0.0469	0.8381	0.9362	0.8844	94	0.8827	0.8563	0.8693	167	1.0	0.9854	0.9926	137	0.9104	0.9196	0.9150	0.9840
0.0426	78.0	7488	0.0467	0.8381	0.9362	0.8844	94	0.8727	0.8623	0.8675	167	1.0	0.9854	0.9926	137	0.9062	0.9221	0.9141	0.9848
0.043	79.0	7584	0.0457	0.8381	0.9362	0.8844	94	0.8735	0.8683	0.8709	167	1.0	0.9854	0.9926	137	0.9064	0.9246	0.9154	0.9854
0.0435	80.0	7680	0.0462	0.8381	0.9362	0.8844	94	0.8727	0.8623	0.8675	167	1.0	0.9854	0.9926	137	0.9062	0.9221	0.9141	0.9851
0.0411	81.0	7776	0.0461	0.8381	0.9362	0.8844	94	0.8606	0.8503	0.8554	167	1.0	0.9854	0.9926	137	0.9012	0.9171	0.9091	0.9843
0.0421	82.0	7872	0.0458	0.8544	0.9362	0.8934	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9104	0.9196	0.9150	0.9843
0.0416	83.0	7968	0.0462	0.8381	0.9362	0.8844	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9082	0.9196	0.9139	0.9843
0.0412	84.0	8064	0.0461	0.8462	0.9362	0.8889	94	0.8788	0.8683	0.8735	167	1.0	0.9854	0.9926	137	0.9109	0.9246	0.9177	0.9851
0.0428	85.0	8160	0.0465	0.8462	0.9362	0.8889	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9104	0.9196	0.9150	0.9845
0.0434	86.0	8256	0.0467	0.8381	0.9362	0.8844	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9840
0.0411	87.0	8352	0.0466	0.8381	0.9362	0.8844	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9840
0.0436	88.0	8448	0.0467	0.8381	0.9362	0.8844	94	0.8780	0.8623	0.8701	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9848
0.0413	89.0	8544	0.0460	0.8544	0.9362	0.8934	94	0.8795	0.8743	0.8769	167	1.0	0.9854	0.9926	137	0.9134	0.9271	0.9202	0.9854
0.0401	90.0	8640	0.0467	0.8462	0.9362	0.8889	94	0.8675	0.8623	0.8649	167	1.0	0.9854	0.9926	137	0.9062	0.9221	0.9141	0.9848
0.0421	91.0	8736	0.0467	0.8462	0.9362	0.8889	94	0.8780	0.8623	0.8701	167	1.0	0.9854	0.9926	137	0.9107	0.9221	0.9164	0.9845
0.0407	92.0	8832	0.0462	0.8462	0.9362	0.8889	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9104	0.9196	0.9150	0.9845
0.0449	93.0	8928	0.0463	0.8462	0.9362	0.8889	94	0.8773	0.8563	0.8667	167	1.0	0.9854	0.9926	137	0.9104	0.9196	0.9150	0.9845
0.0397	94.0	9024	0.0462	0.8381	0.9362	0.8844	94	0.8667	0.8563	0.8614	167	1.0	0.9854	0.9926	137	0.9037	0.9196	0.9116	0.9845
0.0417	95.0	9120	0.0463	0.8381	0.9362	0.8844	94	0.8667	0.8563	0.8614	167	1.0	0.9854	0.9926	137	0.9037	0.9196	0.9116	0.9845
0.0402	96.0	9216	0.0465	0.8381	0.9362	0.8844	94	0.8780	0.8623	0.8701	167	1.0	0.9854	0.9926	137	0.9084	0.9221	0.9152	0.9848
0.0422	97.0	9312	0.0464	0.8462	0.9362	0.8889	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9082	0.9196	0.9139	0.9851
0.0417	98.0	9408	0.0463	0.8462	0.9362	0.8889	94	0.8720	0.8563	0.8640	167	1.0	0.9854	0.9926	137	0.9082	0.9196	0.9139	0.9851
0.0409	99.0	9504	0.0463	0.8462	0.9362	0.8889	94	0.8667	0.8563	0.8614	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9848
0.0404	100.0	9600	0.0463	0.8462	0.9362	0.8889	94	0.8667	0.8563	0.8614	167	1.0	0.9854	0.9926	137	0.9059	0.9196	0.9127	0.9848

Framework versions

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