nerui-pt-pl20-4

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: 0.0559
• Location Precision: 0.9259
• Location Recall: 0.9709
• Location F1: 0.9479
• Location Number: 103
• Organization Precision: 0.9401
• Organization Recall: 0.9181
• Organization F1: 0.9290
• Organization Number: 171
• Person Precision: 0.9695
• Person Recall: 0.9695
• Person F1: 0.9695
• Person Number: 131
• Overall Precision: 0.9458
• Overall Recall: 0.9481
• Overall F1: 0.9470
• 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
0.86	1.0	96	0.4040	0.0	0.0	0.0	103	0.256	0.1871	0.2162	171	0.3254	0.3130	0.3191	131	0.2908	0.1802	0.2226	0.8619
0.3784	2.0	192	0.2618	0.32	0.3107	0.3153	103	0.4785	0.4561	0.4671	171	0.4020	0.6260	0.4896	131	0.4111	0.4741	0.4404	0.9100
0.2322	3.0	288	0.1241	0.7475	0.7184	0.7327	103	0.7	0.7778	0.7368	171	0.9143	0.9771	0.9446	131	0.7809	0.8272	0.8034	0.9633
0.146	4.0	384	0.0837	0.8148	0.8544	0.8341	103	0.7853	0.8772	0.8287	171	0.9624	0.9771	0.9697	131	0.8472	0.9037	0.8746	0.9749
0.1174	5.0	480	0.0715	0.9029	0.9029	0.9029	103	0.8571	0.8772	0.8671	171	0.9481	0.9771	0.9624	131	0.8983	0.9160	0.9071	0.9796
0.1001	6.0	576	0.0610	0.8509	0.9417	0.8940	103	0.8812	0.8246	0.8520	171	0.9699	0.9847	0.9773	131	0.9017	0.9062	0.9039	0.9815
0.0895	7.0	672	0.0543	0.9368	0.8641	0.8990	103	0.8261	0.8889	0.8563	171	0.9773	0.9847	0.9810	131	0.9002	0.9136	0.9069	0.9837
0.0796	8.0	768	0.0474	0.8932	0.8932	0.8932	103	0.8864	0.9123	0.8991	171	0.9771	0.9771	0.9771	131	0.9171	0.9284	0.9227	0.9851
0.0721	9.0	864	0.0444	0.8673	0.9515	0.9074	103	0.9321	0.8830	0.9069	171	0.9771	0.9771	0.9771	131	0.9286	0.9309	0.9297	0.9870
0.0652	10.0	960	0.0419	0.9074	0.9515	0.9289	103	0.9195	0.9357	0.9275	171	0.9771	0.9771	0.9771	131	0.9346	0.9531	0.9438	0.9884
0.0626	11.0	1056	0.0386	0.9340	0.9612	0.9474	103	0.8889	0.9357	0.9117	171	0.9846	0.9771	0.9808	131	0.9303	0.9556	0.9428	0.9881
0.0565	12.0	1152	0.0386	0.9320	0.9320	0.9320	103	0.8914	0.9123	0.9017	171	0.9846	0.9771	0.9808	131	0.9314	0.9383	0.9348	0.9876
0.0561	13.0	1248	0.0392	0.9252	0.9612	0.9429	103	0.9217	0.8947	0.9080	171	0.9695	0.9695	0.9695	131	0.9381	0.9358	0.9370	0.9865
0.0537	14.0	1344	0.0381	0.9259	0.9709	0.9479	103	0.9157	0.8889	0.9021	171	0.9846	0.9771	0.9808	131	0.9406	0.9383	0.9394	0.9854
0.0522	15.0	1440	0.0331	0.9515	0.9515	0.9515	103	0.8966	0.9123	0.9043	171	0.9695	0.9695	0.9695	131	0.9338	0.9407	0.9373	0.9892
0.0466	16.0	1536	0.0356	0.9423	0.9515	0.9469	103	0.9045	0.9415	0.9226	171	0.9692	0.9618	0.9655	131	0.9345	0.9506	0.9425	0.9898
0.0451	17.0	1632	0.0349	0.9252	0.9612	0.9429	103	0.9	0.8947	0.8974	171	0.9846	0.9771	0.9808	131	0.9337	0.9383	0.9360	0.9887
0.0415	18.0	1728	0.0356	0.9074	0.9515	0.9289	103	0.9157	0.8889	0.9021	171	0.9846	0.9771	0.9808	131	0.9356	0.9333	0.9345	0.9876
0.0408	19.0	1824	0.0325	0.9167	0.9612	0.9384	103	0.9176	0.9123	0.9150	171	0.9846	0.9771	0.9808	131	0.9387	0.9457	0.9422	0.9898
0.0392	20.0	1920	0.0368	0.9074	0.9515	0.9289	103	0.9290	0.9181	0.9235	171	0.9846	0.9771	0.9808	131	0.9410	0.9457	0.9433	0.9887
0.037	21.0	2016	0.0467	0.8929	0.9709	0.9302	103	0.9182	0.8538	0.8848	171	0.9695	0.9695	0.9695	131	0.9279	0.9210	0.9244	0.9851
0.0365	22.0	2112	0.0357	0.9083	0.9612	0.9340	103	0.9112	0.9006	0.9059	171	0.9771	0.9771	0.9771	131	0.9315	0.9407	0.9361	0.9876
0.0366	23.0	2208	0.0416	0.8909	0.9515	0.9202	103	0.9036	0.8772	0.8902	171	0.9695	0.9695	0.9695	131	0.9214	0.9259	0.9236	0.9859
0.0355	24.0	2304	0.0415	0.8938	0.9806	0.9352	103	0.9136	0.8655	0.8889	171	0.9692	0.9618	0.9655	131	0.9259	0.9259	0.9259	0.9859
0.0328	25.0	2400	0.0448	0.8783	0.9806	0.9266	103	0.9241	0.8538	0.8875	171	0.9618	0.9618	0.9618	131	0.9233	0.9210	0.9221	0.9843
0.0328	26.0	2496	0.0376	0.9423	0.9515	0.9469	103	0.9181	0.9181	0.9181	171	0.9545	0.9618	0.9582	131	0.9361	0.9407	0.9384	0.9876
0.0315	27.0	2592	0.0348	0.9340	0.9612	0.9474	103	0.9	0.8947	0.8974	171	0.9769	0.9695	0.9732	131	0.9335	0.9358	0.9346	0.9890
0.0292	28.0	2688	0.0356	0.9519	0.9612	0.9565	103	0.9023	0.9181	0.9101	171	0.9692	0.9618	0.9655	131	0.9363	0.9432	0.9397	0.9890
0.0281	29.0	2784	0.0371	0.9174	0.9709	0.9434	103	0.9172	0.9064	0.9118	171	0.9845	0.9695	0.9769	131	0.9386	0.9432	0.9409	0.9881
0.0283	30.0	2880	0.0415	0.9018	0.9806	0.9395	103	0.9235	0.9181	0.9208	171	0.9695	0.9695	0.9695	131	0.9322	0.9506	0.9413	0.9884
0.0264	31.0	2976	0.0383	0.9091	0.9709	0.9390	103	0.9112	0.9006	0.9059	171	0.9844	0.9618	0.9730	131	0.9337	0.9383	0.9360	0.9878
0.0254	32.0	3072	0.0406	0.9167	0.9612	0.9384	103	0.9176	0.9123	0.9150	171	0.9690	0.9542	0.9615	131	0.9337	0.9383	0.9360	0.9873
0.0269	33.0	3168	0.0383	0.9352	0.9806	0.9573	103	0.9401	0.9181	0.9290	171	0.9692	0.9618	0.9655	131	0.9481	0.9481	0.9481	0.9887
0.027	34.0	3264	0.0369	0.9266	0.9806	0.9528	103	0.9123	0.9123	0.9123	171	0.9845	0.9695	0.9769	131	0.9389	0.9481	0.9435	0.9881
0.0284	35.0	3360	0.0364	0.9259	0.9709	0.9479	103	0.9345	0.9181	0.9263	171	0.9621	0.9695	0.9658	131	0.9412	0.9481	0.9446	0.9901
0.0214	36.0	3456	0.0350	0.9182	0.9806	0.9484	103	0.9349	0.9240	0.9294	171	0.9846	0.9771	0.9808	131	0.9462	0.9556	0.9509	0.9903
0.0222	37.0	3552	0.0395	0.9333	0.9515	0.9423	103	0.9123	0.9123	0.9123	171	0.9692	0.9618	0.9655	131	0.9360	0.9383	0.9371	0.9892
0.0232	38.0	3648	0.0444	0.8860	0.9806	0.9309	103	0.9383	0.8889	0.9129	171	0.9771	0.9771	0.9771	131	0.9361	0.9407	0.9384	0.9876
0.0221	39.0	3744	0.0411	0.9182	0.9806	0.9484	103	0.9212	0.8889	0.9048	171	0.9771	0.9771	0.9771	131	0.9384	0.9407	0.9396	0.9890
0.0225	40.0	3840	0.0403	0.9327	0.9417	0.9372	103	0.8960	0.9064	0.9012	171	0.9697	0.9771	0.9734	131	0.9291	0.9383	0.9337	0.9878
0.0233	41.0	3936	0.0363	0.9252	0.9612	0.9429	103	0.9290	0.9181	0.9235	171	0.9771	0.9771	0.9771	131	0.9435	0.9481	0.9458	0.9895
0.0226	42.0	4032	0.0391	0.9333	0.9515	0.9423	103	0.9341	0.9123	0.9231	171	0.9771	0.9771	0.9771	131	0.9479	0.9432	0.9455	0.9901
0.0213	43.0	4128	0.0401	0.9167	0.9612	0.9384	103	0.9217	0.8947	0.9080	171	0.9771	0.9771	0.9771	131	0.9383	0.9383	0.9383	0.9890
0.0197	44.0	4224	0.0417	0.9091	0.9709	0.9390	103	0.9222	0.9006	0.9112	171	0.9771	0.9771	0.9771	131	0.9363	0.9432	0.9397	0.9895
0.0188	45.0	4320	0.0393	0.9174	0.9709	0.9434	103	0.9231	0.9123	0.9176	171	0.9692	0.9618	0.9655	131	0.9363	0.9432	0.9397	0.9890
0.0194	46.0	4416	0.0440	0.8938	0.9806	0.9352	103	0.9096	0.8830	0.8961	171	0.9695	0.9695	0.9695	131	0.9244	0.9358	0.9301	0.9878
0.0185	47.0	4512	0.0407	0.9340	0.9612	0.9474	103	0.9118	0.9064	0.9091	171	0.9695	0.9695	0.9695	131	0.9361	0.9407	0.9384	0.9884
0.018	48.0	4608	0.0461	0.9009	0.9709	0.9346	103	0.9152	0.8830	0.8988	171	0.9771	0.9771	0.9771	131	0.9312	0.9358	0.9335	0.9884
0.0172	49.0	4704	0.0439	0.9252	0.9612	0.9429	103	0.9277	0.9006	0.9139	171	0.9771	0.9771	0.9771	131	0.9431	0.9407	0.9419	0.9890
0.0163	50.0	4800	0.0461	0.8929	0.9709	0.9302	103	0.9152	0.8830	0.8988	171	0.9697	0.9771	0.9734	131	0.9267	0.9358	0.9312	0.9865
0.0174	51.0	4896	0.0474	0.9091	0.9709	0.9390	103	0.9146	0.8772	0.8955	171	0.9771	0.9771	0.9771	131	0.9333	0.9333	0.9333	0.9878
0.0163	52.0	4992	0.0474	0.9259	0.9709	0.9479	103	0.9509	0.9064	0.9281	171	0.9771	0.9771	0.9771	131	0.9527	0.9457	0.9492	0.9895
0.0169	53.0	5088	0.0492	0.9167	0.9612	0.9384	103	0.9273	0.8947	0.9107	171	0.9621	0.9695	0.9658	131	0.9358	0.9358	0.9358	0.9867
0.0161	54.0	5184	0.0482	0.9252	0.9612	0.9429	103	0.9053	0.8947	0.9000	171	0.9771	0.9771	0.9771	131	0.9337	0.9383	0.9360	0.9884
0.0159	55.0	5280	0.0501	0.9099	0.9806	0.9439	103	0.9281	0.9064	0.9172	171	0.9771	0.9771	0.9771	131	0.9389	0.9481	0.9435	0.9884
0.0162	56.0	5376	0.0463	0.9009	0.9709	0.9346	103	0.9202	0.8772	0.8982	171	0.9771	0.9771	0.9771	131	0.9333	0.9333	0.9333	0.9867
0.014	57.0	5472	0.0471	0.9174	0.9709	0.9434	103	0.9268	0.8889	0.9075	171	0.9771	0.9771	0.9771	131	0.9406	0.9383	0.9394	0.9878
0.0138	58.0	5568	0.0450	0.9259	0.9709	0.9479	103	0.9222	0.9006	0.9112	171	0.9846	0.9771	0.9808	131	0.9432	0.9432	0.9432	0.9892
0.0128	59.0	5664	0.0474	0.9252	0.9612	0.9429	103	0.9333	0.9006	0.9167	171	0.9621	0.9695	0.9658	131	0.9406	0.9383	0.9394	0.9890
0.0152	60.0	5760	0.0434	0.9252	0.9612	0.9429	103	0.9217	0.8947	0.9080	171	0.9771	0.9771	0.9771	131	0.9406	0.9383	0.9394	0.9887
0.0138	61.0	5856	0.0472	0.9238	0.9417	0.9327	103	0.9172	0.9064	0.9118	171	0.9695	0.9695	0.9695	131	0.9358	0.9358	0.9358	0.9878
0.0144	62.0	5952	0.0474	0.9245	0.9515	0.9378	103	0.9172	0.9064	0.9118	171	0.9549	0.9695	0.9621	131	0.9314	0.9383	0.9348	0.9881
0.0125	63.0	6048	0.0482	0.9266	0.9806	0.9528	103	0.9172	0.9064	0.9118	171	0.9771	0.9771	0.9771	131	0.9389	0.9481	0.9435	0.9887
0.0128	64.0	6144	0.0458	0.9245	0.9515	0.9378	103	0.9157	0.8889	0.9021	171	0.9695	0.9695	0.9695	131	0.9355	0.9309	0.9332	0.9887
0.0109	65.0	6240	0.0501	0.9245	0.9515	0.9378	103	0.9172	0.9064	0.9118	171	0.9695	0.9695	0.9695	131	0.9360	0.9383	0.9371	0.9884
0.0138	66.0	6336	0.0488	0.9167	0.9612	0.9384	103	0.9226	0.9064	0.9145	171	0.9771	0.9771	0.9771	131	0.9386	0.9432	0.9409	0.9892
0.011	67.0	6432	0.0495	0.9107	0.9903	0.9488	103	0.9394	0.9064	0.9226	171	0.9771	0.9771	0.9771	131	0.9436	0.9506	0.9471	0.9895
0.0124	68.0	6528	0.0516	0.9182	0.9806	0.9484	103	0.9286	0.9123	0.9204	171	0.9771	0.9771	0.9771	131	0.9413	0.9506	0.9459	0.9892
0.0112	69.0	6624	0.0539	0.9266	0.9806	0.9528	103	0.9162	0.8947	0.9053	171	0.9771	0.9771	0.9771	131	0.9386	0.9432	0.9409	0.9884
0.0116	70.0	6720	0.0527	0.9099	0.9806	0.9439	103	0.9398	0.9123	0.9258	171	0.9771	0.9771	0.9771	131	0.9436	0.9506	0.9471	0.9884
0.0126	71.0	6816	0.0553	0.9245	0.9515	0.9378	103	0.9176	0.9123	0.9150	171	0.9695	0.9695	0.9695	131	0.9361	0.9407	0.9384	0.9890
0.0119	72.0	6912	0.0552	0.9252	0.9612	0.9429	103	0.9281	0.9064	0.9172	171	0.9695	0.9695	0.9695	131	0.9407	0.9407	0.9407	0.9878
0.0117	73.0	7008	0.0521	0.9083	0.9612	0.9340	103	0.9167	0.9006	0.9086	171	0.9695	0.9695	0.9695	131	0.9314	0.9383	0.9348	0.9878
0.0109	74.0	7104	0.0524	0.9252	0.9612	0.9429	103	0.9337	0.9064	0.9199	171	0.9695	0.9695	0.9695	131	0.9431	0.9407	0.9419	0.9895
0.0119	75.0	7200	0.0502	0.9252	0.9612	0.9429	103	0.9290	0.9181	0.9235	171	0.9695	0.9695	0.9695	131	0.9410	0.9457	0.9433	0.9890
0.0108	76.0	7296	0.0494	0.9167	0.9612	0.9384	103	0.9290	0.9181	0.9235	171	0.9695	0.9695	0.9695	131	0.9387	0.9457	0.9422	0.9884
0.0102	77.0	7392	0.0562	0.8850	0.9709	0.9259	103	0.9329	0.8947	0.9134	171	0.9695	0.9695	0.9695	131	0.9314	0.9383	0.9348	0.9867
0.0106	78.0	7488	0.0520	0.9252	0.9612	0.9429	103	0.9226	0.9064	0.9145	171	0.9695	0.9695	0.9695	131	0.9384	0.9407	0.9396	0.9884
0.01	79.0	7584	0.0536	0.9252	0.9612	0.9429	103	0.9157	0.8889	0.9021	171	0.9695	0.9695	0.9695	131	0.9356	0.9333	0.9345	0.9878
0.0106	80.0	7680	0.0518	0.9259	0.9709	0.9479	103	0.9222	0.9006	0.9112	171	0.9771	0.9771	0.9771	131	0.9409	0.9432	0.9420	0.9887
0.0109	81.0	7776	0.0509	0.9252	0.9612	0.9429	103	0.9231	0.9123	0.9176	171	0.9771	0.9771	0.9771	131	0.9410	0.9457	0.9433	0.9890
0.0107	82.0	7872	0.0536	0.9259	0.9709	0.9479	103	0.9286	0.9123	0.9204	171	0.9771	0.9771	0.9771	131	0.9435	0.9481	0.9458	0.9890
0.01	83.0	7968	0.0543	0.9174	0.9709	0.9434	103	0.9329	0.8947	0.9134	171	0.9771	0.9771	0.9771	131	0.9431	0.9407	0.9419	0.9878
0.0095	84.0	8064	0.0519	0.9259	0.9709	0.9479	103	0.9345	0.9181	0.9263	171	0.9771	0.9771	0.9771	131	0.9459	0.9506	0.9483	0.9887
0.0089	85.0	8160	0.0534	0.9259	0.9709	0.9479	103	0.9286	0.9123	0.9204	171	0.9846	0.9771	0.9808	131	0.9458	0.9481	0.9470	0.9890
0.0092	86.0	8256	0.0564	0.9174	0.9709	0.9434	103	0.9268	0.8889	0.9075	171	0.9771	0.9771	0.9771	131	0.9406	0.9383	0.9394	0.9873
0.009	87.0	8352	0.0552	0.9252	0.9612	0.9429	103	0.9281	0.9064	0.9172	171	0.9695	0.9695	0.9695	131	0.9407	0.9407	0.9407	0.9878
0.0091	88.0	8448	0.0558	0.9252	0.9612	0.9429	103	0.9341	0.9123	0.9231	171	0.9695	0.9695	0.9695	131	0.9432	0.9432	0.9432	0.9881
0.0084	89.0	8544	0.0564	0.9259	0.9709	0.9479	103	0.9341	0.9123	0.9231	171	0.9771	0.9771	0.9771	131	0.9458	0.9481	0.9470	0.9887
0.0083	90.0	8640	0.0559	0.9259	0.9709	0.9479	103	0.9341	0.9123	0.9231	171	0.9771	0.9771	0.9771	131	0.9458	0.9481	0.9470	0.9884
0.0091	91.0	8736	0.0571	0.9252	0.9612	0.9429	103	0.9337	0.9064	0.9199	171	0.9695	0.9695	0.9695	131	0.9431	0.9407	0.9419	0.9878
0.0091	92.0	8832	0.0549	0.9252	0.9612	0.9429	103	0.9398	0.9123	0.9258	171	0.9695	0.9695	0.9695	131	0.9455	0.9432	0.9444	0.9878
0.0087	93.0	8928	0.0556	0.9252	0.9612	0.9429	103	0.9341	0.9123	0.9231	171	0.9695	0.9695	0.9695	131	0.9432	0.9432	0.9432	0.9881
0.01	94.0	9024	0.0554	0.9252	0.9612	0.9429	103	0.9341	0.9123	0.9231	171	0.9695	0.9695	0.9695	131	0.9432	0.9432	0.9432	0.9881
0.0084	95.0	9120	0.0553	0.9252	0.9612	0.9429	103	0.9341	0.9123	0.9231	171	0.9695	0.9695	0.9695	131	0.9432	0.9432	0.9432	0.9881
0.0087	96.0	9216	0.0561	0.9259	0.9709	0.9479	103	0.9345	0.9181	0.9263	171	0.9695	0.9695	0.9695	131	0.9435	0.9481	0.9458	0.9884
0.0085	97.0	9312	0.0559	0.9259	0.9709	0.9479	103	0.9401	0.9181	0.9290	171	0.9695	0.9695	0.9695	131	0.9458	0.9481	0.9470	0.9887
0.0096	98.0	9408	0.0556	0.9252	0.9612	0.9429	103	0.9341	0.9123	0.9231	171	0.9695	0.9695	0.9695	131	0.9432	0.9432	0.9432	0.9884
0.0077	99.0	9504	0.0558	0.9252	0.9612	0.9429	103	0.9341	0.9123	0.9231	171	0.9695	0.9695	0.9695	131	0.9432	0.9432	0.9432	0.9884
0.0093	100.0	9600	0.0559	0.9259	0.9709	0.9479	103	0.9401	0.9181	0.9290	171	0.9695	0.9695	0.9695	131	0.9458	0.9481	0.9470	0.9887

Framework versions

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