nerui-pt-pl30-0

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: 0.0581
• Location Precision: 0.8713
• Location Recall: 0.9362
• Location F1: 0.9026
• Location Number: 94
• Organization Precision: 0.9217
• Organization Recall: 0.9162
• Organization F1: 0.9189
• Organization Number: 167
• Person Precision: 0.9926
• Person Recall: 0.9854
• Person F1: 0.9890
• Person Number: 137
• Overall Precision: 0.9330
• Overall Recall: 0.9447
• Overall F1: 0.9388
• Overall Accuracy: 0.9878

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
0.8686	1.0	96	0.4168	0.0	0.0	0.0	94	0.1788	0.1916	0.1850	167	0.2365	0.3504	0.2824	137	0.2083	0.2010	0.2046	0.8588
0.3777	2.0	192	0.2543	0.4839	0.3191	0.3846	94	0.4678	0.6527	0.5450	167	0.6416	0.8102	0.7161	137	0.5342	0.6281	0.5774	0.9215
0.2087	3.0	288	0.1150	0.7404	0.8191	0.7778	94	0.7053	0.8024	0.7507	167	0.9241	0.9781	0.9504	137	0.7859	0.8668	0.8244	0.9652
0.1366	4.0	384	0.0908	0.7456	0.9043	0.8173	94	0.7625	0.7305	0.7462	167	0.9315	0.9927	0.9611	137	0.8167	0.8618	0.8386	0.9691
0.116	5.0	480	0.0718	0.8687	0.9149	0.8912	94	0.8171	0.8024	0.8097	167	0.9507	0.9854	0.9677	137	0.8765	0.8920	0.8842	0.9760
0.0965	6.0	576	0.0544	0.8491	0.9574	0.9	94	0.8820	0.8503	0.8659	167	0.9783	0.9854	0.9818	137	0.9062	0.9221	0.9141	0.9809
0.0853	7.0	672	0.0533	0.7982	0.9681	0.875	94	0.8650	0.8443	0.8545	167	0.9926	0.9781	0.9853	137	0.8883	0.9196	0.9037	0.9809
0.0797	8.0	768	0.0470	0.8585	0.9681	0.91	94	0.8683	0.8683	0.8683	167	0.9853	0.9781	0.9817	137	0.9046	0.9296	0.9170	0.9840
0.0702	9.0	864	0.0443	0.8103	1.0	0.8952	94	0.9091	0.8383	0.8723	167	0.9926	0.9854	0.9890	137	0.9089	0.9271	0.9179	0.9859
0.07	10.0	960	0.0377	0.9583	0.9787	0.9684	94	0.8778	0.9461	0.9107	167	0.9854	0.9854	0.9854	137	0.9322	0.9673	0.9494	0.9884
0.063	11.0	1056	0.0344	0.9020	0.9787	0.9388	94	0.9202	0.8982	0.9091	167	0.9854	0.9854	0.9854	137	0.9378	0.9472	0.9425	0.9898
0.0565	12.0	1152	0.0435	0.8835	0.9681	0.9239	94	0.8935	0.9042	0.8988	167	0.9852	0.9708	0.9779	137	0.9214	0.9422	0.9317	0.9859
0.056	13.0	1248	0.0390	0.8846	0.9787	0.9293	94	0.9299	0.8743	0.9012	167	0.9781	0.9781	0.9781	137	0.9347	0.9347	0.9347	0.9876
0.0516	14.0	1344	0.0421	0.8774	0.9894	0.93	94	0.9187	0.8802	0.8991	167	0.9708	0.9708	0.9708	137	0.9256	0.9372	0.9313	0.9865
0.0485	15.0	1440	0.0335	0.9278	0.9574	0.9424	94	0.9080	0.9461	0.9267	167	0.9710	0.9781	0.9745	137	0.9340	0.9598	0.9467	0.9892
0.046	16.0	1536	0.0352	0.8952	1.0	0.9447	94	0.9551	0.8922	0.9226	167	0.9853	0.9781	0.9817	137	0.9496	0.9472	0.9484	0.9895
0.0448	17.0	1632	0.0377	0.8932	0.9787	0.9340	94	0.9245	0.8802	0.9018	167	0.9853	0.9781	0.9817	137	0.9372	0.9372	0.9372	0.9873
0.0409	18.0	1728	0.0506	0.8198	0.9681	0.8878	94	0.9586	0.8323	0.8910	167	0.9781	0.9781	0.9781	137	0.9262	0.9146	0.9204	0.9834
0.0376	19.0	1824	0.0369	0.8911	0.9574	0.9231	94	0.9620	0.9102	0.9354	167	0.9926	0.9854	0.9890	137	0.9544	0.9472	0.9508	0.9892
0.0382	20.0	1920	0.0413	0.8426	0.9681	0.9010	94	0.9494	0.8982	0.9231	167	0.9854	0.9854	0.9854	137	0.9330	0.9447	0.9388	0.9876
0.0364	21.0	2016	0.0353	0.9010	0.9681	0.9333	94	0.9387	0.9162	0.9273	167	0.9926	0.9854	0.9890	137	0.9475	0.9523	0.9499	0.9895
0.036	22.0	2112	0.0393	0.8932	0.9787	0.9340	94	0.9273	0.9162	0.9217	167	0.9781	0.9781	0.9781	137	0.9358	0.9523	0.9440	0.9884
0.0356	23.0	2208	0.0451	0.875	0.9681	0.9192	94	0.9608	0.8802	0.9188	167	0.9926	0.9854	0.9890	137	0.9491	0.9372	0.9431	0.9870
0.0322	24.0	2304	0.0394	0.8911	0.9574	0.9231	94	0.9441	0.9102	0.9268	167	0.9926	0.9854	0.9890	137	0.9472	0.9472	0.9472	0.9878
0.0342	25.0	2400	0.0412	0.9	0.9574	0.9278	94	0.9064	0.9281	0.9172	167	0.9853	0.9781	0.9817	137	0.9312	0.9523	0.9416	0.9867
0.0309	26.0	2496	0.0488	0.8835	0.9681	0.9239	94	0.9152	0.9042	0.9096	167	0.9926	0.9781	0.9853	137	0.9330	0.9447	0.9388	0.9856
0.0282	27.0	2592	0.0389	0.91	0.9681	0.9381	94	0.9277	0.9222	0.9249	167	0.9926	0.9854	0.9890	137	0.9453	0.9548	0.95	0.9892
0.0267	28.0	2688	0.0472	0.8426	0.9681	0.9010	94	0.9255	0.8922	0.9085	167	0.9926	0.9854	0.9890	137	0.9259	0.9422	0.9340	0.9873
0.0298	29.0	2784	0.0428	0.8585	0.9681	0.91	94	0.9367	0.8862	0.9108	167	0.9926	0.9854	0.9890	137	0.935	0.9397	0.9373	0.9876
0.0262	30.0	2880	0.0428	0.8835	0.9681	0.9239	94	0.9394	0.9281	0.9337	167	0.9926	0.9854	0.9890	137	0.9431	0.9573	0.9501	0.9892
0.0273	31.0	2976	0.0426	0.8932	0.9787	0.9340	94	0.9321	0.9042	0.9179	167	0.9926	0.9854	0.9890	137	0.9426	0.9497	0.9462	0.9892
0.0253	32.0	3072	0.0451	0.8738	0.9574	0.9137	94	0.9085	0.8922	0.9003	167	0.9926	0.9854	0.9890	137	0.9280	0.9397	0.9338	0.9876
0.0265	33.0	3168	0.0524	0.8558	0.9468	0.8990	94	0.8963	0.8802	0.8882	167	0.9853	0.9781	0.9817	137	0.9158	0.9296	0.9227	0.9854
0.0236	34.0	3264	0.0478	0.8713	0.9362	0.9026	94	0.925	0.8862	0.9052	167	0.9926	0.9854	0.9890	137	0.9345	0.9322	0.9333	0.9870
0.0207	35.0	3360	0.0490	0.9091	0.9574	0.9326	94	0.9387	0.9162	0.9273	167	0.9926	0.9854	0.9890	137	0.9497	0.9497	0.9497	0.9887
0.0208	36.0	3456	0.0438	0.8824	0.9574	0.9184	94	0.9325	0.9102	0.9212	167	0.9853	0.9781	0.9817	137	0.9377	0.9447	0.9412	0.9881
0.0217	37.0	3552	0.0479	0.8667	0.9681	0.9146	94	0.9157	0.9102	0.9129	167	0.9926	0.9854	0.9890	137	0.9287	0.9497	0.9391	0.9876
0.0205	38.0	3648	0.0443	0.9	0.9574	0.9278	94	0.9341	0.9341	0.9341	167	0.9926	0.9854	0.9890	137	0.9454	0.9573	0.9513	0.9892
0.02	39.0	3744	0.0443	0.875	0.9681	0.9192	94	0.9317	0.8982	0.9146	167	0.9926	0.9854	0.9890	137	0.9377	0.9447	0.9412	0.9870
0.0196	40.0	3840	0.0395	0.91	0.9681	0.9381	94	0.9329	0.9162	0.9245	167	0.9926	0.9854	0.9890	137	0.9475	0.9523	0.9499	0.9901
0.0193	41.0	3936	0.0481	0.8835	0.9681	0.9239	94	0.9325	0.9102	0.9212	167	0.9926	0.9854	0.9890	137	0.9403	0.9497	0.9450	0.9881
0.0192	42.0	4032	0.0455	0.9010	0.9681	0.9333	94	0.9394	0.9281	0.9337	167	0.9926	0.9854	0.9890	137	0.9478	0.9573	0.9525	0.9895
0.018	43.0	4128	0.0534	0.8738	0.9574	0.9137	94	0.9437	0.9042	0.9235	167	1.0	0.9854	0.9926	137	0.9447	0.9447	0.9447	0.9867
0.0177	44.0	4224	0.0550	0.8585	0.9681	0.91	94	0.9437	0.9042	0.9235	167	0.9926	0.9854	0.9890	137	0.9378	0.9472	0.9425	0.9867
0.0169	45.0	4320	0.0428	0.8812	0.9468	0.9128	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.9375	0.9422	0.9398	0.9895
0.0171	46.0	4416	0.0421	0.8812	0.9468	0.9128	94	0.9212	0.9102	0.9157	167	0.9854	0.9854	0.9854	137	0.9330	0.9447	0.9388	0.9890
0.0165	47.0	4512	0.0455	0.8738	0.9574	0.9137	94	0.9152	0.9042	0.9096	167	0.9926	0.9854	0.9890	137	0.9307	0.9447	0.9377	0.9887
0.0149	48.0	4608	0.0550	0.8544	0.9362	0.8934	94	0.8976	0.8922	0.8949	167	0.9853	0.9781	0.9817	137	0.9160	0.9322	0.9240	0.9859
0.0164	49.0	4704	0.0566	0.8571	0.9574	0.9045	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.9307	0.9447	0.9377	0.9870
0.015	50.0	4800	0.0552	0.8614	0.9255	0.8923	94	0.9202	0.8982	0.9091	167	0.9853	0.9781	0.9817	137	0.9275	0.9322	0.9298	0.9865
0.0152	51.0	4896	0.0557	0.8544	0.9362	0.8934	94	0.9198	0.8922	0.9058	167	0.9853	0.9781	0.9817	137	0.9252	0.9322	0.9287	0.9870
0.0155	52.0	4992	0.0474	0.87	0.9255	0.8969	94	0.9333	0.9222	0.9277	167	0.9926	0.9781	0.9853	137	0.9375	0.9422	0.9398	0.9890
0.0155	53.0	5088	0.0503	0.8713	0.9362	0.9026	94	0.9441	0.9102	0.9268	167	0.9926	0.9854	0.9890	137	0.9422	0.9422	0.9422	0.9878
0.013	54.0	5184	0.0518	0.8713	0.9362	0.9026	94	0.9273	0.9162	0.9217	167	0.9926	0.9854	0.9890	137	0.9353	0.9447	0.94	0.9878
0.0145	55.0	5280	0.0493	0.8911	0.9574	0.9231	94	0.9383	0.9102	0.9240	167	0.9926	0.9854	0.9890	137	0.9449	0.9472	0.9460	0.9887
0.013	56.0	5376	0.0440	0.8812	0.9468	0.9128	94	0.9202	0.8982	0.9091	167	0.9779	0.9708	0.9744	137	0.93	0.9347	0.9323	0.9887
0.0126	57.0	5472	0.0475	0.8725	0.9468	0.9082	94	0.9212	0.9102	0.9157	167	0.9853	0.9781	0.9817	137	0.9305	0.9422	0.9363	0.9876
0.0142	58.0	5568	0.0420	0.88	0.9362	0.9072	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.9373	0.9397	0.9385	0.9887
0.0113	59.0	5664	0.0637	0.8788	0.9255	0.9016	94	0.9048	0.9102	0.9075	167	0.9853	0.9781	0.9817	137	0.9256	0.9372	0.9313	0.9865
0.0121	60.0	5760	0.0527	0.8641	0.9468	0.9036	94	0.9157	0.9102	0.9129	167	0.9926	0.9854	0.9890	137	0.9284	0.9447	0.9365	0.9870
0.0115	61.0	5856	0.0488	0.8776	0.9149	0.8958	94	0.9286	0.9341	0.9313	167	0.9926	0.9854	0.9890	137	0.9378	0.9472	0.9425	0.9881
0.0112	62.0	5952	0.0552	0.8571	0.9574	0.9045	94	0.9329	0.9162	0.9245	167	0.9926	0.9854	0.9890	137	0.9333	0.9497	0.9415	0.9881
0.0102	63.0	6048	0.0470	0.8878	0.9255	0.9062	94	0.9059	0.9222	0.9139	167	0.9926	0.9854	0.9890	137	0.9307	0.9447	0.9377	0.9881
0.0123	64.0	6144	0.0571	0.8544	0.9362	0.8934	94	0.9268	0.9102	0.9184	167	0.9926	0.9854	0.9890	137	0.9305	0.9422	0.9363	0.9876
0.0122	65.0	6240	0.0566	0.8713	0.9362	0.9026	94	0.9273	0.9162	0.9217	167	0.9926	0.9854	0.9890	137	0.9353	0.9447	0.94	0.9876
0.0104	66.0	6336	0.0602	0.8182	0.9574	0.8824	94	0.9484	0.8802	0.9130	167	0.9926	0.9854	0.9890	137	0.9277	0.9347	0.9312	0.9865
0.0107	67.0	6432	0.0545	0.8738	0.9574	0.9137	94	0.9212	0.9102	0.9157	167	0.9926	0.9854	0.9890	137	0.9332	0.9472	0.9401	0.9876
0.0103	68.0	6528	0.0484	0.8911	0.9574	0.9231	94	0.9162	0.9162	0.9162	167	0.9926	0.9854	0.9890	137	0.9356	0.9497	0.9426	0.9884
0.0113	69.0	6624	0.0464	0.8627	0.9362	0.8980	94	0.9207	0.9042	0.9124	167	0.9926	0.9854	0.9890	137	0.9303	0.9397	0.9350	0.9873
0.0101	70.0	6720	0.0502	0.8866	0.9149	0.9005	94	0.9112	0.9222	0.9167	167	0.9926	0.9854	0.9890	137	0.9328	0.9422	0.9375	0.9881
0.0095	71.0	6816	0.0554	0.8641	0.9468	0.9036	94	0.9152	0.9042	0.9096	167	0.9926	0.9854	0.9890	137	0.9282	0.9422	0.9352	0.9876
0.0098	72.0	6912	0.0588	0.8641	0.9468	0.9036	94	0.9333	0.9222	0.9277	167	0.9926	0.9854	0.9890	137	0.9356	0.9497	0.9426	0.9870
0.0095	73.0	7008	0.0593	0.8824	0.9574	0.9184	94	0.9333	0.9222	0.9277	167	0.9926	0.9854	0.9890	137	0.9404	0.9523	0.9463	0.9878
0.0093	74.0	7104	0.0541	0.8544	0.9362	0.8934	94	0.9390	0.9222	0.9305	167	0.9926	0.9854	0.9890	137	0.9355	0.9472	0.9413	0.9881
0.0083	75.0	7200	0.0563	0.8544	0.9362	0.8934	94	0.9333	0.9222	0.9277	167	0.9926	0.9854	0.9890	137	0.9332	0.9472	0.9401	0.9881
0.0093	76.0	7296	0.0562	0.8462	0.9362	0.8889	94	0.9207	0.9042	0.9124	167	0.9926	0.9854	0.9890	137	0.9257	0.9397	0.9327	0.9873
0.0094	77.0	7392	0.0549	0.8571	0.9574	0.9045	94	0.95	0.9102	0.9297	167	0.9926	0.9854	0.9890	137	0.9401	0.9472	0.9437	0.9881
0.0082	78.0	7488	0.0549	0.87	0.9255	0.8969	94	0.9226	0.9281	0.9254	167	0.9926	0.9854	0.9890	137	0.9332	0.9472	0.9401	0.9878
0.0084	79.0	7584	0.0584	0.8627	0.9362	0.8980	94	0.9321	0.9042	0.9179	167	0.9853	0.9781	0.9817	137	0.9325	0.9372	0.9348	0.9878
0.0087	80.0	7680	0.0553	0.8544	0.9362	0.8934	94	0.9506	0.9222	0.9362	167	0.9926	0.9854	0.9890	137	0.9401	0.9472	0.9437	0.9890
0.0084	81.0	7776	0.0600	0.8571	0.9574	0.9045	94	0.9157	0.9102	0.9129	167	0.9853	0.9781	0.9817	137	0.9238	0.9447	0.9342	0.9870
0.0075	82.0	7872	0.0540	0.8788	0.9255	0.9016	94	0.9162	0.9162	0.9162	167	0.9854	0.9854	0.9854	137	0.9305	0.9422	0.9363	0.9878
0.008	83.0	7968	0.0577	0.8641	0.9468	0.9036	94	0.9268	0.9102	0.9184	167	0.9854	0.9854	0.9854	137	0.9307	0.9447	0.9377	0.9878
0.0077	84.0	8064	0.0613	0.8641	0.9468	0.9036	94	0.9222	0.9222	0.9222	167	0.9926	0.9854	0.9890	137	0.9310	0.9497	0.9403	0.9878
0.0061	85.0	8160	0.0596	0.8529	0.9255	0.8878	94	0.9268	0.9102	0.9184	167	0.9853	0.9781	0.9817	137	0.9279	0.9372	0.9325	0.9873
0.0069	86.0	8256	0.0556	0.8476	0.9468	0.8945	94	0.9273	0.9162	0.9217	167	0.9853	0.9781	0.9817	137	0.9261	0.9447	0.9353	0.9878
0.0071	87.0	8352	0.0579	0.8969	0.9255	0.9110	94	0.9181	0.9401	0.9290	167	0.9853	0.9781	0.9817	137	0.9356	0.9497	0.9426	0.9881
0.008	88.0	8448	0.0609	0.8411	0.9574	0.8955	94	0.9259	0.8982	0.9119	167	0.9854	0.9854	0.9854	137	0.9236	0.9422	0.9328	0.9873
0.0072	89.0	8544	0.0579	0.8713	0.9362	0.9026	94	0.9217	0.9162	0.9189	167	0.9853	0.9781	0.9817	137	0.9305	0.9422	0.9363	0.9881
0.0071	90.0	8640	0.0551	0.8738	0.9574	0.9137	94	0.9390	0.9222	0.9305	167	0.9926	0.9854	0.9890	137	0.9404	0.9523	0.9463	0.9892
0.0082	91.0	8736	0.0543	0.8738	0.9574	0.9137	94	0.9333	0.9222	0.9277	167	0.9926	0.9854	0.9890	137	0.9381	0.9523	0.9451	0.9890
0.0076	92.0	8832	0.0563	0.8738	0.9574	0.9137	94	0.9277	0.9222	0.9249	167	0.9926	0.9854	0.9890	137	0.9358	0.9523	0.9440	0.9887
0.0067	93.0	8928	0.0573	0.8812	0.9468	0.9128	94	0.9281	0.9281	0.9281	167	0.9926	0.9854	0.9890	137	0.9381	0.9523	0.9451	0.9884
0.0062	94.0	9024	0.0569	0.8654	0.9574	0.9091	94	0.9333	0.9222	0.9277	167	0.9926	0.9854	0.9890	137	0.9358	0.9523	0.9440	0.9887
0.0077	95.0	9120	0.0549	0.8725	0.9468	0.9082	94	0.9333	0.9222	0.9277	167	0.9926	0.9854	0.9890	137	0.9380	0.9497	0.9438	0.9890
0.0072	96.0	9216	0.0581	0.8713	0.9362	0.9026	94	0.9222	0.9222	0.9222	167	0.9926	0.9854	0.9890	137	0.9332	0.9472	0.9401	0.9878
0.0067	97.0	9312	0.0567	0.8725	0.9468	0.9082	94	0.9217	0.9162	0.9189	167	0.9854	0.9854	0.9854	137	0.9309	0.9472	0.9390	0.9881
0.0071	98.0	9408	0.0572	0.88	0.9362	0.9072	94	0.9277	0.9222	0.9249	167	0.9926	0.9854	0.9890	137	0.9378	0.9472	0.9425	0.9884
0.0063	99.0	9504	0.0579	0.8713	0.9362	0.9026	94	0.9217	0.9162	0.9189	167	0.9926	0.9854	0.9890	137	0.9330	0.9447	0.9388	0.9878
0.0073	100.0	9600	0.0581	0.8713	0.9362	0.9026	94	0.9217	0.9162	0.9189	167	0.9926	0.9854	0.9890	137	0.9330	0.9447	0.9388	0.9878

Framework versions

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