nerui-lora-r16-4

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: 0.0460
• Location Precision: 0.8596
• Location Recall: 0.9515
• Location F1: 0.9032
• Location Number: 103
• Organization Precision: 0.9018
• Organization Recall: 0.8596
• Organization F1: 0.8802
• Organization Number: 171
• Person Precision: 0.9621
• Person Recall: 0.9695
• Person F1: 0.9658
• Person Number: 131
• Overall Precision: 0.9095
• Overall Recall: 0.9185
• Overall F1: 0.9140
• Overall Accuracy: 0.9843

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
1.0754	1.0	96	0.6777	0.0	0.0	0.0	103	0.0	0.0	0.0	171	0.0	0.0	0.0	131	0.0	0.0	0.0	0.8373
0.6397	2.0	192	0.5210	0.0	0.0	0.0	103	0.0	0.0	0.0	171	0.0	0.0	0.0	131	0.0	0.0	0.0	0.8382
0.4876	3.0	288	0.3655	0.2333	0.0680	0.1053	103	0.3084	0.1930	0.2374	171	0.2721	0.2824	0.2772	131	0.2821	0.1901	0.2271	0.8732
0.3447	4.0	384	0.2576	0.4167	0.3398	0.3743	103	0.4977	0.6199	0.5521	171	0.4751	0.6565	0.5513	131	0.4749	0.5605	0.5142	0.9227
0.2489	5.0	480	0.1880	0.5652	0.5049	0.5333	103	0.6291	0.7836	0.6979	171	0.7197	0.8626	0.7847	131	0.6472	0.7383	0.6897	0.9484
0.1922	6.0	576	0.1418	0.7379	0.7379	0.7379	103	0.75	0.8421	0.7934	171	0.8865	0.9542	0.9191	131	0.7913	0.8519	0.8205	0.9635
0.1585	7.0	672	0.1196	0.7364	0.7864	0.7606	103	0.7526	0.8538	0.8	171	0.9	0.9618	0.9299	131	0.7950	0.8716	0.8316	0.9638
0.1378	8.0	768	0.1014	0.8058	0.8058	0.8058	103	0.7760	0.8713	0.8209	171	0.9270	0.9695	0.9478	131	0.8310	0.8864	0.8578	0.9696
0.1249	9.0	864	0.0929	0.8113	0.8350	0.8230	103	0.7696	0.8596	0.8122	171	0.9203	0.9695	0.9442	131	0.8276	0.8889	0.8571	0.9713
0.1157	10.0	960	0.0842	0.8416	0.8252	0.8333	103	0.7824	0.8830	0.8297	171	0.9065	0.9618	0.9333	131	0.8360	0.8938	0.8640	0.9718
0.106	11.0	1056	0.0774	0.8462	0.8544	0.8502	103	0.8022	0.8538	0.8272	171	0.9403	0.9618	0.9509	131	0.8571	0.8889	0.8727	0.9751
0.1021	12.0	1152	0.0777	0.8505	0.8835	0.8667	103	0.8118	0.8830	0.8459	171	0.9065	0.9618	0.9333	131	0.8519	0.9086	0.8793	0.9754
0.0959	13.0	1248	0.0699	0.8654	0.8738	0.8696	103	0.8678	0.8830	0.8754	171	0.9474	0.9618	0.9545	131	0.8929	0.9062	0.8995	0.9790
0.0915	14.0	1344	0.0697	0.8667	0.8835	0.8750	103	0.875	0.8596	0.8673	171	0.9403	0.9618	0.9509	131	0.8943	0.8988	0.8966	0.9787
0.0875	15.0	1440	0.0640	0.875	0.8835	0.8792	103	0.8263	0.9181	0.8698	171	0.9333	0.9618	0.9474	131	0.8718	0.9235	0.8969	0.9785
0.0837	16.0	1536	0.0616	0.8624	0.9126	0.8868	103	0.8280	0.9006	0.8627	171	0.9478	0.9695	0.9585	131	0.8741	0.9259	0.8993	0.9796
0.0799	17.0	1632	0.0570	0.8942	0.9029	0.8986	103	0.8387	0.9123	0.8739	171	0.9549	0.9695	0.9621	131	0.8889	0.9284	0.9082	0.9804
0.0763	18.0	1728	0.0549	0.8785	0.9126	0.8952	103	0.8603	0.9006	0.8800	171	0.9695	0.9695	0.9695	131	0.8993	0.9259	0.9124	0.9807
0.0732	19.0	1824	0.0561	0.8857	0.9029	0.8942	103	0.8837	0.8889	0.8863	171	0.9695	0.9695	0.9695	131	0.9118	0.9185	0.9151	0.9818
0.072	20.0	1920	0.0518	0.8868	0.9126	0.8995	103	0.8626	0.9181	0.8895	171	0.9846	0.9771	0.9808	131	0.9067	0.9358	0.9210	0.9820
0.069	21.0	2016	0.0508	0.8598	0.8932	0.8762	103	0.9107	0.8947	0.9027	171	0.9695	0.9695	0.9695	131	0.9163	0.9185	0.9174	0.9832
0.0681	22.0	2112	0.0510	0.8704	0.9126	0.8910	103	0.8495	0.9240	0.8852	171	0.9846	0.9771	0.9808	131	0.8962	0.9383	0.9168	0.9829
0.068	23.0	2208	0.0487	0.8704	0.9126	0.8910	103	0.8960	0.9064	0.9012	171	0.9846	0.9771	0.9808	131	0.9173	0.9309	0.9240	0.9845
0.0646	24.0	2304	0.0502	0.8333	0.9223	0.8756	103	0.9080	0.8655	0.8862	171	0.9545	0.9618	0.9582	131	0.9022	0.9111	0.9066	0.9820
0.0641	25.0	2400	0.0478	0.8532	0.9029	0.8774	103	0.8902	0.9006	0.8953	171	0.9695	0.9695	0.9695	131	0.9056	0.9235	0.9144	0.9845
0.0632	26.0	2496	0.0462	0.8846	0.8932	0.8889	103	0.8736	0.9298	0.9008	171	0.9695	0.9695	0.9695	131	0.9065	0.9333	0.9197	0.9851
0.0591	27.0	2592	0.0447	0.8774	0.9029	0.8900	103	0.8908	0.9064	0.8986	171	0.9695	0.9695	0.9695	131	0.9124	0.9259	0.9191	0.9854
0.0586	28.0	2688	0.0448	0.8857	0.9029	0.8942	103	0.8851	0.9006	0.8928	171	0.9695	0.9695	0.9695	131	0.9122	0.9235	0.9178	0.9859
0.0558	29.0	2784	0.0440	0.9208	0.9029	0.9118	103	0.8764	0.9123	0.8940	171	0.9621	0.9695	0.9658	131	0.9148	0.9284	0.9216	0.9862
0.0568	30.0	2880	0.0453	0.8942	0.9029	0.8986	103	0.9006	0.9006	0.9006	171	0.9695	0.9695	0.9695	131	0.9212	0.9235	0.9223	0.9854
0.0547	31.0	2976	0.0436	0.8868	0.9126	0.8995	103	0.8715	0.9123	0.8914	171	0.9695	0.9695	0.9695	131	0.9062	0.9309	0.9184	0.9851
0.0544	32.0	3072	0.0434	0.8796	0.9223	0.9005	103	0.9036	0.8772	0.8902	171	0.9695	0.9695	0.9695	131	0.9185	0.9185	0.9185	0.9859
0.0509	33.0	3168	0.0450	0.8545	0.9126	0.8826	103	0.9187	0.8596	0.8882	171	0.9695	0.9695	0.9695	131	0.9177	0.9086	0.9132	0.9848
0.05	34.0	3264	0.0419	0.8846	0.8932	0.8889	103	0.9112	0.9006	0.9059	171	0.9846	0.9771	0.9808	131	0.9280	0.9235	0.9257	0.9865
0.0496	35.0	3360	0.0427	0.8482	0.9223	0.8837	103	0.8994	0.8889	0.8941	171	0.9695	0.9695	0.9695	131	0.9078	0.9235	0.9155	0.9848
0.0504	36.0	3456	0.0433	0.8468	0.9126	0.8785	103	0.9198	0.8713	0.8949	171	0.9695	0.9695	0.9695	131	0.9158	0.9136	0.9147	0.9856
0.0485	37.0	3552	0.0429	0.9038	0.9126	0.9082	103	0.8764	0.9123	0.8940	171	0.9695	0.9695	0.9695	131	0.9128	0.9309	0.9218	0.9854
0.0466	38.0	3648	0.0439	0.8692	0.9029	0.8857	103	0.8988	0.8830	0.8909	171	0.9695	0.9695	0.9695	131	0.9138	0.9160	0.9149	0.9848
0.0464	39.0	3744	0.0425	0.8649	0.9320	0.8972	103	0.9096	0.8830	0.8961	171	0.9695	0.9695	0.9695	131	0.9167	0.9235	0.9200	0.9856
0.0457	40.0	3840	0.0429	0.8952	0.9126	0.9038	103	0.8941	0.8889	0.8915	171	0.9695	0.9695	0.9695	131	0.9187	0.9210	0.9199	0.9856
0.0454	41.0	3936	0.0413	0.9029	0.9029	0.9029	103	0.8764	0.9123	0.8940	171	0.9695	0.9695	0.9695	131	0.9126	0.9284	0.9204	0.9856
0.0446	42.0	4032	0.0433	0.8962	0.9223	0.9091	103	0.8941	0.8889	0.8915	171	0.9695	0.9695	0.9695	131	0.9189	0.9235	0.9212	0.9859
0.0461	43.0	4128	0.0432	0.8636	0.9223	0.8920	103	0.9	0.8947	0.8974	171	0.9695	0.9695	0.9695	131	0.9124	0.9259	0.9191	0.9851
0.0445	44.0	4224	0.0451	0.8571	0.9320	0.8930	103	0.8817	0.8713	0.8765	171	0.9695	0.9695	0.9695	131	0.9029	0.9185	0.9106	0.9843
0.0439	45.0	4320	0.0427	0.8796	0.9223	0.9005	103	0.9096	0.8830	0.8961	171	0.9695	0.9695	0.9695	131	0.9210	0.9210	0.9210	0.9859
0.0436	46.0	4416	0.0450	0.8348	0.9320	0.8807	103	0.9136	0.8655	0.8889	171	0.9695	0.9695	0.9695	131	0.9093	0.9160	0.9127	0.9851
0.0436	47.0	4512	0.0410	0.9029	0.9029	0.9029	103	0.8807	0.9064	0.8934	171	0.9695	0.9695	0.9695	131	0.9146	0.9259	0.9202	0.9859
0.0418	48.0	4608	0.0459	0.8348	0.9320	0.8807	103	0.9198	0.8713	0.8949	171	0.9695	0.9695	0.9695	131	0.9118	0.9185	0.9151	0.9851
0.0393	49.0	4704	0.0438	0.8348	0.9320	0.8807	103	0.9024	0.8655	0.8836	171	0.9695	0.9695	0.9695	131	0.9049	0.9160	0.9104	0.9843
0.0403	50.0	4800	0.0465	0.8407	0.9223	0.8796	103	0.8916	0.8655	0.8783	171	0.9695	0.9695	0.9695	131	0.9024	0.9136	0.9080	0.9840
0.0397	51.0	4896	0.0455	0.8496	0.9320	0.8889	103	0.9193	0.8655	0.8916	171	0.9695	0.9695	0.9695	131	0.9160	0.9160	0.9160	0.9848
0.0398	52.0	4992	0.0427	0.8952	0.9126	0.9038	103	0.88	0.9006	0.8902	171	0.9695	0.9695	0.9695	131	0.9124	0.9259	0.9191	0.9859
0.0394	53.0	5088	0.0449	0.8584	0.9417	0.8981	103	0.9080	0.8655	0.8862	171	0.9695	0.9695	0.9695	131	0.9140	0.9185	0.9163	0.9851
0.0378	54.0	5184	0.0420	0.8785	0.9126	0.8952	103	0.8743	0.8947	0.8844	171	0.9695	0.9695	0.9695	131	0.9056	0.9235	0.9144	0.9859
0.0387	55.0	5280	0.0446	0.8727	0.9320	0.9014	103	0.8922	0.8713	0.8817	171	0.9695	0.9695	0.9695	131	0.9118	0.9185	0.9151	0.9851
0.0369	56.0	5376	0.0435	0.8559	0.9223	0.8879	103	0.8765	0.8713	0.8739	171	0.9695	0.9695	0.9695	131	0.9005	0.9160	0.9082	0.9845
0.0383	57.0	5472	0.0433	0.8661	0.9417	0.9023	103	0.8929	0.8772	0.8850	171	0.9695	0.9695	0.9695	131	0.9100	0.9235	0.9167	0.9854
0.0368	58.0	5568	0.0444	0.8807	0.9320	0.9057	103	0.8889	0.8889	0.8889	171	0.9695	0.9695	0.9695	131	0.9124	0.9259	0.9191	0.9859
0.0349	59.0	5664	0.0451	0.8624	0.9126	0.8868	103	0.8757	0.8655	0.8706	171	0.9695	0.9695	0.9695	131	0.9022	0.9111	0.9066	0.9843
0.0357	60.0	5760	0.0455	0.8716	0.9223	0.8962	103	0.8855	0.8596	0.8724	171	0.9695	0.9695	0.9695	131	0.9089	0.9111	0.9100	0.9843
0.0365	61.0	5856	0.0456	0.8673	0.9515	0.9074	103	0.9018	0.8596	0.8802	171	0.9695	0.9695	0.9695	131	0.9140	0.9185	0.9163	0.9851
0.0365	62.0	5952	0.0455	0.8462	0.9612	0.9	103	0.9080	0.8655	0.8862	171	0.9695	0.9695	0.9695	131	0.9100	0.9235	0.9167	0.9851
0.034	63.0	6048	0.0424	0.8584	0.9417	0.8981	103	0.8817	0.8713	0.8765	171	0.9695	0.9695	0.9695	131	0.9031	0.9210	0.9120	0.9848
0.0347	64.0	6144	0.0465	0.8596	0.9515	0.9032	103	0.9074	0.8596	0.8829	171	0.9695	0.9695	0.9695	131	0.9140	0.9185	0.9163	0.9848
0.0342	65.0	6240	0.0446	0.8522	0.9515	0.8991	103	0.9085	0.8713	0.8896	171	0.9695	0.9695	0.9695	131	0.9122	0.9235	0.9178	0.9851
0.034	66.0	6336	0.0450	0.8684	0.9612	0.9124	103	0.9080	0.8655	0.8862	171	0.9695	0.9695	0.9695	131	0.9167	0.9235	0.9200	0.9856
0.0338	67.0	6432	0.0458	0.8596	0.9515	0.9032	103	0.9024	0.8655	0.8836	171	0.9695	0.9695	0.9695	131	0.9120	0.9210	0.9165	0.9851
0.0368	68.0	6528	0.0461	0.8571	0.9320	0.8930	103	0.8909	0.8596	0.875	171	0.9846	0.9771	0.9808	131	0.9115	0.9160	0.9138	0.9843
0.036	69.0	6624	0.0454	0.8571	0.9320	0.8930	103	0.8909	0.8596	0.875	171	0.9621	0.9695	0.9658	131	0.9046	0.9136	0.9091	0.9840
0.0318	70.0	6720	0.0479	0.8584	0.9417	0.8981	103	0.9080	0.8655	0.8862	171	0.9695	0.9695	0.9695	131	0.9140	0.9185	0.9163	0.9843
0.0327	71.0	6816	0.0449	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9845
0.0328	72.0	6912	0.0490	0.8596	0.9515	0.9032	103	0.8957	0.8538	0.8743	171	0.9621	0.9695	0.9658	131	0.9071	0.9160	0.9115	0.9843
0.0325	73.0	7008	0.0465	0.8673	0.9515	0.9074	103	0.9080	0.8655	0.8862	171	0.9621	0.9695	0.9658	131	0.9142	0.9210	0.9176	0.9848
0.0337	74.0	7104	0.0479	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9837
0.0329	75.0	7200	0.0460	0.8727	0.9320	0.9014	103	0.8963	0.8596	0.8776	171	0.9695	0.9695	0.9695	131	0.9136	0.9136	0.9136	0.9845
0.0308	76.0	7296	0.0472	0.8522	0.9515	0.8991	103	0.9130	0.8596	0.8855	171	0.9695	0.9695	0.9695	131	0.9140	0.9185	0.9163	0.9845
0.0319	77.0	7392	0.0474	0.8522	0.9515	0.8991	103	0.9074	0.8596	0.8829	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9840
0.0317	78.0	7488	0.0454	0.8496	0.9320	0.8889	103	0.8963	0.8596	0.8776	171	0.9771	0.9771	0.9771	131	0.9093	0.9160	0.9127	0.9837
0.0305	79.0	7584	0.0459	0.8496	0.9320	0.8889	103	0.8909	0.8596	0.875	171	0.9621	0.9695	0.9658	131	0.9024	0.9136	0.9080	0.9837
0.0302	80.0	7680	0.0458	0.8496	0.9320	0.8889	103	0.8855	0.8596	0.8724	171	0.9621	0.9695	0.9658	131	0.9002	0.9136	0.9069	0.9837
0.0315	81.0	7776	0.0453	0.8496	0.9320	0.8889	103	0.8855	0.8596	0.8724	171	0.9621	0.9695	0.9658	131	0.9002	0.9136	0.9069	0.9837
0.031	82.0	7872	0.0448	0.8509	0.9417	0.8940	103	0.8963	0.8596	0.8776	171	0.9621	0.9695	0.9658	131	0.9049	0.9160	0.9104	0.9843
0.0322	83.0	7968	0.0446	0.8596	0.9515	0.9032	103	0.9074	0.8596	0.8829	171	0.9695	0.9695	0.9695	131	0.9140	0.9185	0.9163	0.9848
0.0292	84.0	8064	0.0446	0.8496	0.9320	0.8889	103	0.8855	0.8596	0.8724	171	0.9621	0.9695	0.9658	131	0.9002	0.9136	0.9069	0.9837
0.0302	85.0	8160	0.0443	0.8522	0.9515	0.8991	103	0.9024	0.8655	0.8836	171	0.9621	0.9695	0.9658	131	0.9075	0.9210	0.9142	0.9848
0.0298	86.0	8256	0.0455	0.8522	0.9515	0.8991	103	0.9074	0.8596	0.8829	171	0.9695	0.9695	0.9695	131	0.9118	0.9185	0.9151	0.9845
0.0311	87.0	8352	0.0451	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9845
0.0302	88.0	8448	0.0441	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9848
0.0295	89.0	8544	0.0448	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9843
0.0299	90.0	8640	0.0448	0.8509	0.9417	0.8940	103	0.8963	0.8596	0.8776	171	0.9621	0.9695	0.9658	131	0.9049	0.9160	0.9104	0.9840
0.0301	91.0	8736	0.0455	0.8596	0.9515	0.9032	103	0.8963	0.8596	0.8776	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9843
0.03	92.0	8832	0.0463	0.8596	0.9515	0.9032	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9843
0.0275	93.0	8928	0.0454	0.8596	0.9515	0.9032	103	0.8963	0.8596	0.8776	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9843
0.0311	94.0	9024	0.0462	0.8596	0.9515	0.9032	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9840
0.0285	95.0	9120	0.0458	0.8596	0.9515	0.9032	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9843
0.0304	96.0	9216	0.0459	0.8596	0.9515	0.9032	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9843
0.0285	97.0	9312	0.0460	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9840
0.0299	98.0	9408	0.0462	0.8522	0.9515	0.8991	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9073	0.9185	0.9129	0.9840
0.0296	99.0	9504	0.0461	0.8596	0.9515	0.9032	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9843
0.0279	100.0	9600	0.0460	0.8596	0.9515	0.9032	103	0.9018	0.8596	0.8802	171	0.9621	0.9695	0.9658	131	0.9095	0.9185	0.9140	0.9843

Framework versions

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