nerui-base-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: 0.1084
• Location Precision: 0.89
• Location Recall: 0.9468
• Location F1: 0.9175
• Location Number: 94
• Organization Precision: 0.9387
• Organization Recall: 0.9162
• Organization F1: 0.9273
• Organization Number: 167
• Person Precision: 1.0
• Person Recall: 0.9781
• Person F1: 0.9889
• Person Number: 137
• Overall Precision: 0.9471
• Overall Recall: 0.9447
• Overall F1: 0.9459
• Overall Accuracy: 0.9887

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
0.2566	1.0	96	0.0455	0.9634	0.8404	0.8977	94	0.8333	0.9281	0.8782	167	0.9708	0.9708	0.9708	137	0.9062	0.9221	0.9141	0.9843
0.0617	2.0	192	0.0519	0.8381	0.9362	0.8844	94	0.8896	0.8683	0.8788	167	0.9926	0.9781	0.9853	137	0.9107	0.9221	0.9164	0.9834
0.0356	3.0	288	0.0534	0.9062	0.9255	0.9158	94	0.8211	0.9341	0.8739	167	1.0	0.9708	0.9852	137	0.8974	0.9447	0.9204	0.9840
0.0235	4.0	384	0.0525	0.8866	0.9149	0.9005	94	0.9006	0.9222	0.9112	167	1.0	0.9781	0.9889	137	0.9303	0.9397	0.9350	0.9856
0.0156	5.0	480	0.0623	0.9032	0.8936	0.8984	94	0.9333	0.9222	0.9277	167	0.9926	0.9781	0.9853	137	0.9466	0.9347	0.9406	0.9873
0.0101	6.0	576	0.0590	0.9043	0.9043	0.9043	94	0.8929	0.8982	0.8955	167	0.9926	0.9781	0.9853	137	0.9295	0.9271	0.9283	0.9859
0.0091	7.0	672	0.0955	0.8036	0.9574	0.8738	94	0.9211	0.8383	0.8777	167	0.9643	0.9854	0.9747	137	0.9035	0.9171	0.9102	0.9809
0.0084	8.0	768	0.0871	0.8365	0.9255	0.8788	94	0.9062	0.8683	0.8869	167	1.0	0.9781	0.9889	137	0.9196	0.9196	0.9196	0.9826
0.007	9.0	864	0.0629	0.9565	0.9362	0.9462	94	0.8895	0.9162	0.9027	167	1.0	0.9854	0.9926	137	0.9424	0.9447	0.9435	0.9881
0.0047	10.0	960	0.0564	0.9167	0.9362	0.9263	94	0.9512	0.9341	0.9426	167	1.0	0.9781	0.9889	137	0.9594	0.9497	0.9545	0.9901
0.0043	11.0	1056	0.0829	0.9158	0.9255	0.9206	94	0.8708	0.9281	0.8986	167	0.9926	0.9781	0.9853	137	0.9216	0.9447	0.9330	0.9856
0.0034	12.0	1152	0.0779	0.9247	0.9149	0.9198	94	0.8667	0.9341	0.8991	167	0.9926	0.9781	0.9853	137	0.9216	0.9447	0.9330	0.9865
0.0047	13.0	1248	0.0781	0.8922	0.9681	0.9286	94	0.95	0.9102	0.9297	167	0.9854	0.9854	0.9854	137	0.9474	0.9497	0.9486	0.9862
0.006	14.0	1344	0.0682	0.9271	0.9468	0.9368	94	0.9236	0.8683	0.8951	167	1.0	0.9781	0.9889	137	0.9509	0.9246	0.9376	0.9859
0.0031	15.0	1440	0.0759	0.9149	0.9149	0.9149	94	0.8814	0.9341	0.9070	167	0.9926	0.9781	0.9853	137	0.9261	0.9447	0.9353	0.9878
0.0049	16.0	1536	0.0801	0.9082	0.9468	0.9271	94	0.9107	0.9162	0.9134	167	0.9574	0.9854	0.9712	137	0.9263	0.9472	0.9366	0.9865
0.0036	17.0	1632	0.0933	0.9278	0.9574	0.9424	94	0.9333	0.9222	0.9277	167	0.9853	0.9781	0.9817	137	0.9497	0.9497	0.9497	0.9887
0.0033	18.0	1728	0.0828	0.9167	0.9362	0.9263	94	0.9167	0.9222	0.9194	167	0.9926	0.9781	0.9853	137	0.9424	0.9447	0.9435	0.9870
0.0031	19.0	1824	0.0819	0.9149	0.9149	0.9149	94	0.9102	0.9102	0.9102	167	0.9708	0.9708	0.9708	137	0.9322	0.9322	0.9322	0.9873
0.0025	20.0	1920	0.0871	0.8969	0.9255	0.9110	94	0.9321	0.9042	0.9179	167	0.9708	0.9708	0.9708	137	0.9369	0.9322	0.9345	0.9878
0.0023	21.0	2016	0.0813	0.89	0.9468	0.9175	94	0.9162	0.9162	0.9162	167	0.9706	0.9635	0.9670	137	0.9280	0.9397	0.9338	0.9873
0.0023	22.0	2112	0.0885	0.9158	0.9255	0.9206	94	0.8814	0.9341	0.9070	167	1.0	0.9635	0.9814	137	0.9282	0.9422	0.9352	0.9867
0.0018	23.0	2208	0.1209	0.8788	0.9255	0.9016	94	0.8947	0.9162	0.9053	167	0.9779	0.9708	0.9744	137	0.9187	0.9372	0.9279	0.9837
0.0036	24.0	2304	0.0841	0.9175	0.9468	0.9319	94	0.9029	0.9461	0.9240	167	0.9853	0.9781	0.9817	137	0.9338	0.9573	0.9454	0.9878
0.0034	25.0	2400	0.0860	0.9368	0.9468	0.9418	94	0.9186	0.9461	0.9322	167	0.9926	0.9781	0.9853	137	0.9478	0.9573	0.9525	0.9884
0.0029	26.0	2496	0.0684	0.9381	0.9681	0.9529	94	0.9176	0.9341	0.9258	167	0.9926	0.9781	0.9853	137	0.9478	0.9573	0.9525	0.9898
0.0031	27.0	2592	0.1158	0.9278	0.9574	0.9424	94	0.8933	0.9521	0.9217	167	0.9926	0.9781	0.9853	137	0.9341	0.9623	0.9480	0.9865
0.0045	28.0	2688	0.0860	0.9263	0.9362	0.9312	94	0.8963	0.8802	0.8882	167	0.9926	0.9781	0.9853	137	0.9365	0.9271	0.9318	0.9854
0.0018	29.0	2784	0.0869	0.9271	0.9468	0.9368	94	0.9290	0.9401	0.9345	167	0.9926	0.9781	0.9853	137	0.95	0.9548	0.9524	0.9884
0.0023	30.0	2880	0.1042	0.9184	0.9574	0.9375	94	0.9394	0.9281	0.9337	167	1.0	0.9781	0.9889	137	0.9547	0.9523	0.9535	0.9881
0.0028	31.0	2976	0.1003	0.9020	0.9787	0.9388	94	0.9118	0.9281	0.9199	167	0.9853	0.9781	0.9817	137	0.9338	0.9573	0.9454	0.9862
0.0015	32.0	3072	0.0802	0.91	0.9681	0.9381	94	0.9353	0.9521	0.9436	167	0.9853	0.9781	0.9817	137	0.9458	0.9648	0.9552	0.9890
0.0025	33.0	3168	0.0959	0.8667	0.9681	0.9146	94	0.9375	0.8982	0.9174	167	1.0	0.9781	0.9889	137	0.9398	0.9422	0.9410	0.9862
0.0014	34.0	3264	0.0970	0.9184	0.9574	0.9375	94	0.9286	0.9341	0.9313	167	1.0	0.9781	0.9889	137	0.95	0.9548	0.9524	0.9881
0.0017	35.0	3360	0.0790	0.9570	0.9468	0.9519	94	0.9123	0.9341	0.9231	167	0.9926	0.9781	0.9853	137	0.9499	0.9523	0.9511	0.9890
0.002	36.0	3456	0.0912	0.9010	0.9681	0.9333	94	0.9317	0.8982	0.9146	167	0.9853	0.9781	0.9817	137	0.9422	0.9422	0.9422	0.9870
0.0025	37.0	3552	0.1061	0.9271	0.9468	0.9368	94	0.9030	0.8922	0.8976	167	1.0	0.9781	0.9889	137	0.9418	0.9347	0.9382	0.9865
0.0028	38.0	3648	0.0982	0.9184	0.9574	0.9375	94	0.9085	0.8922	0.9003	167	1.0	0.9781	0.9889	137	0.9419	0.9372	0.9395	0.9870
0.0022	39.0	3744	0.1061	0.8969	0.9255	0.9110	94	0.8953	0.9222	0.9086	167	1.0	0.9781	0.9889	137	0.9305	0.9422	0.9363	0.9848
0.0018	40.0	3840	0.1077	0.8980	0.9362	0.9167	94	0.9202	0.8982	0.9091	167	1.0	0.9781	0.9889	137	0.9418	0.9347	0.9382	0.9862
0.002	41.0	3936	0.0923	0.8980	0.9362	0.9167	94	0.9325	0.9102	0.9212	167	1.0	0.9781	0.9889	137	0.9468	0.9397	0.9433	0.9870
0.003	42.0	4032	0.0899	0.9053	0.9149	0.9101	94	0.9112	0.9222	0.9167	167	0.9853	0.9781	0.9817	137	0.935	0.9397	0.9373	0.9862
0.0027	43.0	4128	0.0827	0.9355	0.9255	0.9305	94	0.9277	0.9222	0.9249	167	1.0	0.9781	0.9889	137	0.9542	0.9422	0.9482	0.9878
0.0015	44.0	4224	0.0798	0.9149	0.9149	0.9149	94	0.9102	0.9102	0.9102	167	1.0	0.9781	0.9889	137	0.9418	0.9347	0.9382	0.9878
0.0011	45.0	4320	0.0868	0.8958	0.9149	0.9053	94	0.9313	0.8922	0.9113	167	0.9853	0.9781	0.9817	137	0.9413	0.9271	0.9342	0.9881
0.0012	46.0	4416	0.0743	0.8922	0.9681	0.9286	94	0.9679	0.9042	0.9350	167	0.9852	0.9708	0.9779	137	0.9542	0.9422	0.9482	0.9903
0.0012	47.0	4512	0.0870	0.9072	0.9362	0.9215	94	0.9375	0.8982	0.9174	167	0.9853	0.9781	0.9817	137	0.9466	0.9347	0.9406	0.9884
0.0019	48.0	4608	0.0759	0.89	0.9468	0.9175	94	0.9308	0.8862	0.9080	167	0.9779	0.9708	0.9744	137	0.9367	0.9296	0.9332	0.9881
0.0015	49.0	4704	0.0810	0.9271	0.9468	0.9368	94	0.9176	0.9341	0.9258	167	1.0	0.9781	0.9889	137	0.9475	0.9523	0.9499	0.9895
0.0011	50.0	4800	0.0890	0.9082	0.9468	0.9271	94	0.9506	0.9222	0.9362	167	0.9853	0.9781	0.9817	137	0.9520	0.9472	0.9496	0.9890
0.0007	51.0	4896	0.0827	0.9167	0.9362	0.9263	94	0.9341	0.9341	0.9341	167	0.9853	0.9781	0.9817	137	0.9474	0.9497	0.9486	0.9895
0.001	52.0	4992	0.0873	0.8980	0.9362	0.9167	94	0.9281	0.9281	0.9281	167	0.9926	0.9781	0.9853	137	0.9425	0.9472	0.9449	0.9887
0.001	53.0	5088	0.0820	0.8980	0.9362	0.9167	94	0.9394	0.9281	0.9337	167	0.9852	0.9708	0.9779	137	0.9447	0.9447	0.9447	0.9890
0.0004	54.0	5184	0.0917	0.8911	0.9574	0.9231	94	0.9434	0.8982	0.9202	167	0.9853	0.9781	0.9817	137	0.9444	0.9397	0.9421	0.9867
0.0006	55.0	5280	0.1053	0.8980	0.9362	0.9167	94	0.9333	0.9222	0.9277	167	0.9926	0.9781	0.9853	137	0.9447	0.9447	0.9447	0.9884
0.001	56.0	5376	0.1040	0.8990	0.9468	0.9223	94	0.9333	0.9222	0.9277	167	0.9853	0.9781	0.9817	137	0.9425	0.9472	0.9449	0.9881
0.0005	57.0	5472	0.1042	0.8990	0.9468	0.9223	94	0.9337	0.9281	0.9309	167	0.9926	0.9781	0.9853	137	0.945	0.9497	0.9474	0.9884
0.0009	58.0	5568	0.1057	0.9082	0.9468	0.9271	94	0.9202	0.8982	0.9091	167	0.9853	0.9781	0.9817	137	0.9395	0.9372	0.9384	0.9876
0.001	59.0	5664	0.1034	0.8911	0.9574	0.9231	94	0.9277	0.9222	0.9249	167	1.0	0.9781	0.9889	137	0.9426	0.9497	0.9462	0.9873
0.0012	60.0	5760	0.0910	0.9072	0.9362	0.9215	94	0.9337	0.9281	0.9309	167	0.9779	0.9708	0.9744	137	0.9424	0.9447	0.9435	0.9887
0.0008	61.0	5856	0.0987	0.9247	0.9149	0.9198	94	0.9102	0.9102	0.9102	167	0.9779	0.9708	0.9744	137	0.9369	0.9322	0.9345	0.9862
0.0005	62.0	5952	0.1056	0.8889	0.9362	0.9119	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9470	0.9422	0.9446	0.9876
0.0006	63.0	6048	0.1050	0.8980	0.9362	0.9167	94	0.9268	0.9102	0.9184	167	0.9926	0.9781	0.9853	137	0.9421	0.9397	0.9409	0.9873
0.0013	64.0	6144	0.0956	0.9072	0.9362	0.9215	94	0.9329	0.9162	0.9245	167	1.0	0.9781	0.9889	137	0.9494	0.9422	0.9458	0.9884
0.0006	65.0	6240	0.1061	0.9082	0.9468	0.9271	94	0.9313	0.8922	0.9113	167	1.0	0.9781	0.9889	137	0.9490	0.9347	0.9418	0.9854
0.0008	66.0	6336	0.1032	0.8980	0.9362	0.9167	94	0.9325	0.9102	0.9212	167	0.9926	0.9781	0.9853	137	0.9444	0.9397	0.9421	0.9881
0.0004	67.0	6432	0.0961	0.8980	0.9362	0.9167	94	0.9273	0.9162	0.9217	167	1.0	0.9781	0.9889	137	0.9446	0.9422	0.9434	0.9890
0.0008	68.0	6528	0.0979	0.88	0.9362	0.9072	94	0.925	0.8862	0.9052	167	0.9926	0.9781	0.9853	137	0.9367	0.9296	0.9332	0.9870
0.0013	69.0	6624	0.1021	0.89	0.9468	0.9175	94	0.9162	0.9162	0.9162	167	1.0	0.9781	0.9889	137	0.9377	0.9447	0.9412	0.9870
0.0004	70.0	6720	0.0933	0.88	0.9362	0.9072	94	0.9264	0.9042	0.9152	167	1.0	0.9781	0.9889	137	0.9395	0.9372	0.9384	0.9881
0.001	71.0	6816	0.0892	0.8788	0.9255	0.9016	94	0.9264	0.9042	0.9152	167	0.9852	0.9708	0.9779	137	0.9345	0.9322	0.9333	0.9881
0.0006	72.0	6912	0.0966	0.9091	0.9574	0.9326	94	0.9509	0.9281	0.9394	167	0.9926	0.9781	0.9853	137	0.9547	0.9523	0.9535	0.9892
0.0006	73.0	7008	0.0997	0.8911	0.9574	0.9231	94	0.9441	0.9102	0.9268	167	1.0	0.9781	0.9889	137	0.9495	0.9447	0.9471	0.9884
0.0004	74.0	7104	0.1035	0.8824	0.9574	0.9184	94	0.9497	0.9042	0.9264	167	0.9926	0.9781	0.9853	137	0.9470	0.9422	0.9446	0.9881
0.0005	75.0	7200	0.1036	0.8788	0.9255	0.9016	94	0.9371	0.8922	0.9141	167	0.9852	0.9708	0.9779	137	0.9389	0.9271	0.9330	0.9870
0.0004	76.0	7296	0.0978	0.8788	0.9255	0.9016	94	0.9317	0.8982	0.9146	167	0.9638	0.9708	0.9673	137	0.9296	0.9296	0.9296	0.9867
0.0004	77.0	7392	0.0896	0.88	0.9362	0.9072	94	0.9273	0.9162	0.9217	167	0.9926	0.9781	0.9853	137	0.9375	0.9422	0.9398	0.9887
0.0007	78.0	7488	0.1034	0.8889	0.9362	0.9119	94	0.9308	0.8862	0.9080	167	1.0	0.9781	0.9889	137	0.9439	0.9296	0.9367	0.9878
0.0004	79.0	7584	0.1117	0.8812	0.9468	0.9128	94	0.9259	0.8982	0.9119	167	1.0	0.9781	0.9889	137	0.9395	0.9372	0.9384	0.9873
0.0006	80.0	7680	0.1053	0.8980	0.9362	0.9167	94	0.9017	0.9341	0.9176	167	1.0	0.9781	0.9889	137	0.9333	0.9497	0.9415	0.9873
0.0003	81.0	7776	0.1023	0.8980	0.9362	0.9167	94	0.9222	0.9222	0.9222	167	1.0	0.9781	0.9889	137	0.9424	0.9447	0.9435	0.9884
0.0005	82.0	7872	0.0998	0.8990	0.9468	0.9223	94	0.9281	0.9281	0.9281	167	1.0	0.9781	0.9889	137	0.945	0.9497	0.9474	0.9887
0.0004	83.0	7968	0.1031	0.8980	0.9362	0.9167	94	0.9222	0.9222	0.9222	167	1.0	0.9781	0.9889	137	0.9424	0.9447	0.9435	0.9884
0.0002	84.0	8064	0.1076	0.9072	0.9362	0.9215	94	0.9273	0.9162	0.9217	167	1.0	0.9781	0.9889	137	0.9470	0.9422	0.9446	0.9890
0.0008	85.0	8160	0.1031	0.9062	0.9255	0.9158	94	0.9273	0.9162	0.9217	167	0.9925	0.9708	0.9815	137	0.9443	0.9372	0.9407	0.9887
0.0003	86.0	8256	0.0967	0.9062	0.9255	0.9158	94	0.9383	0.9102	0.9240	167	0.9925	0.9708	0.9815	137	0.9490	0.9347	0.9418	0.9892
0.0005	87.0	8352	0.0978	0.8889	0.9362	0.9119	94	0.9317	0.8982	0.9146	167	1.0	0.9781	0.9889	137	0.9442	0.9347	0.9394	0.9884
0.0003	88.0	8448	0.1104	0.8889	0.9362	0.9119	94	0.9375	0.8982	0.9174	167	1.0	0.9781	0.9889	137	0.9466	0.9347	0.9406	0.9881
0.0005	89.0	8544	0.1069	0.89	0.9468	0.9175	94	0.9441	0.9102	0.9268	167	1.0	0.9781	0.9889	137	0.9494	0.9422	0.9458	0.9887
0.0003	90.0	8640	0.1071	0.89	0.9468	0.9175	94	0.9441	0.9102	0.9268	167	1.0	0.9781	0.9889	137	0.9494	0.9422	0.9458	0.9887
0.0005	91.0	8736	0.1068	0.89	0.9468	0.9175	94	0.9441	0.9102	0.9268	167	1.0	0.9781	0.9889	137	0.9494	0.9422	0.9458	0.9887
0.0004	92.0	8832	0.1078	0.89	0.9468	0.9175	94	0.9444	0.9162	0.9301	167	1.0	0.9781	0.9889	137	0.9495	0.9447	0.9471	0.9890
0.0003	93.0	8928	0.1079	0.89	0.9468	0.9175	94	0.9444	0.9162	0.9301	167	1.0	0.9781	0.9889	137	0.9495	0.9447	0.9471	0.9890
0.0004	94.0	9024	0.1082	0.89	0.9468	0.9175	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9471	0.9447	0.9459	0.9887
0.0003	95.0	9120	0.1080	0.89	0.9468	0.9175	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9471	0.9447	0.9459	0.9887
0.0003	96.0	9216	0.1082	0.89	0.9468	0.9175	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9471	0.9447	0.9459	0.9887
0.0002	97.0	9312	0.1080	0.89	0.9468	0.9175	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9471	0.9447	0.9459	0.9887
0.0003	98.0	9408	0.1080	0.89	0.9468	0.9175	94	0.9444	0.9162	0.9301	167	1.0	0.9781	0.9889	137	0.9495	0.9447	0.9471	0.9890
0.0003	99.0	9504	0.1085	0.89	0.9468	0.9175	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9471	0.9447	0.9459	0.9887
0.0002	100.0	9600	0.1084	0.89	0.9468	0.9175	94	0.9387	0.9162	0.9273	167	1.0	0.9781	0.9889	137	0.9471	0.9447	0.9459	0.9887

Framework versions

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