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apwic/
nerui-pt-pl5-2

Name: nerui-pt-pl5-2
Availability: InStock

generated_from_trainer

indolem/indobert-base-uncased

finetune

mit

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nerui-pt-pl5-2

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: 0.0678
Location Precision: 0.9255
Location Recall: 0.9355
Location F1: 0.9305
Location Number: 93
Organization Precision: 0.9162
Organization Recall: 0.9217
Organization F1: 0.9189
Organization Number: 166
Person Precision: 0.9718
Person Recall: 0.9718
Person F1: 0.9718
Person Number: 142
Overall Precision: 0.9380
Overall Recall: 0.9426
Overall F1: 0.9403
Overall Accuracy: 0.9877

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
0.881	1.0	96	0.3962	0.3333	0.0108	0.0208	93	0.2688	0.3012	0.2841	166	0.2834	0.3732	0.3222	142	0.2766	0.2594	0.2677	0.8672
0.3506	2.0	192	0.1969	0.3094	0.4624	0.3707	93	0.64	0.6747	0.6569	166	0.6437	0.7887	0.7089	142	0.5471	0.6658	0.6007	0.9418
0.1965	3.0	288	0.1110	0.7470	0.6667	0.7045	93	0.6591	0.8735	0.7513	166	0.9459	0.9859	0.9655	142	0.7694	0.8653	0.8146	0.9638
0.1379	4.0	384	0.0912	0.6957	0.8602	0.7692	93	0.7772	0.8614	0.8171	166	0.9792	0.9930	0.9860	142	0.8217	0.9077	0.8626	0.9701
0.1107	5.0	480	0.0687	0.8265	0.8710	0.8482	93	0.8268	0.8916	0.8580	166	0.9722	0.9859	0.9790	142	0.8765	0.9202	0.8978	0.9794
0.0972	6.0	576	0.0764	0.7213	0.9462	0.8186	93	0.8618	0.7892	0.8239	166	0.9789	0.9789	0.9789	142	0.8606	0.8928	0.8764	0.9759
0.086	7.0	672	0.0620	0.8265	0.8710	0.8482	93	0.8158	0.9337	0.8708	166	0.9655	0.9859	0.9756	142	0.8684	0.9377	0.9017	0.9789
0.0786	8.0	768	0.0522	0.8131	0.9355	0.8700	93	0.8539	0.9157	0.8837	166	0.9857	0.9718	0.9787	142	0.8871	0.9401	0.9128	0.9835
0.0709	9.0	864	0.0522	0.7757	0.8925	0.83	93	0.8820	0.8554	0.8685	166	0.9857	0.9718	0.9787	142	0.8897	0.9052	0.8974	0.9808
0.0665	10.0	960	0.0494	0.8	0.9032	0.8485	93	0.8895	0.9217	0.9053	166	0.9720	0.9789	0.9754	142	0.8952	0.9377	0.9160	0.9838
0.0598	11.0	1056	0.0489	0.8333	0.9140	0.8718	93	0.8793	0.9217	0.9	166	0.9787	0.9718	0.9753	142	0.9017	0.9377	0.9193	0.9838
0.0584	12.0	1152	0.0502	0.8485	0.9032	0.875	93	0.8844	0.9217	0.9027	166	0.9718	0.9718	0.9718	142	0.9058	0.9352	0.9202	0.9849
0.0536	13.0	1248	0.0502	0.8673	0.9140	0.8901	93	0.9136	0.8916	0.9024	166	0.9787	0.9718	0.9753	142	0.9252	0.9252	0.9252	0.9855
0.0519	14.0	1344	0.0527	0.9043	0.9140	0.9091	93	0.9198	0.8976	0.9085	166	0.9789	0.9789	0.9789	142	0.9372	0.9302	0.9337	0.9855
0.0507	15.0	1440	0.0450	0.8788	0.9355	0.9062	93	0.9255	0.8976	0.9113	166	0.9789	0.9789	0.9789	142	0.9328	0.9352	0.9340	0.9879
0.0451	16.0	1536	0.0458	0.8529	0.9355	0.8923	93	0.9321	0.9096	0.9207	166	0.9718	0.9718	0.9718	142	0.9261	0.9377	0.9318	0.9866
0.0438	17.0	1632	0.0516	0.8381	0.9462	0.8889	93	0.9313	0.8976	0.9141	166	0.9650	0.9718	0.9684	142	0.9191	0.9352	0.9271	0.9860
0.0415	18.0	1728	0.0491	0.8866	0.9247	0.9053	93	0.9085	0.8976	0.9030	166	0.9650	0.9718	0.9684	142	0.9233	0.9302	0.9267	0.9866
0.04	19.0	1824	0.0481	0.9348	0.9247	0.9297	93	0.9167	0.9277	0.9222	166	0.9650	0.9718	0.9684	142	0.9380	0.9426	0.9403	0.9879
0.0383	20.0	1920	0.0501	0.9175	0.9570	0.9368	93	0.9394	0.9337	0.9366	166	0.9650	0.9718	0.9684	142	0.9432	0.9526	0.9479	0.9890
0.0391	21.0	2016	0.0523	0.8462	0.9462	0.8934	93	0.9255	0.8976	0.9113	166	0.9718	0.9718	0.9718	142	0.9214	0.9352	0.9282	0.9860
0.0353	22.0	2112	0.0451	0.8980	0.9462	0.9215	93	0.9231	0.9398	0.9313	166	0.9787	0.9718	0.9753	142	0.9363	0.9526	0.9444	0.9890
0.0356	23.0	2208	0.0490	0.9062	0.9355	0.9206	93	0.9112	0.9277	0.9194	166	0.9650	0.9718	0.9684	142	0.9289	0.9451	0.9370	0.9874
0.0333	24.0	2304	0.0491	0.8641	0.9570	0.9082	93	0.9576	0.9518	0.9547	166	0.9718	0.9718	0.9718	142	0.9390	0.9601	0.9494	0.9885
0.033	25.0	2400	0.0544	0.8990	0.9570	0.9271	93	0.9152	0.9096	0.9124	166	0.9718	0.9718	0.9718	142	0.9310	0.9426	0.9368	0.9852
0.0333	26.0	2496	0.0555	0.9247	0.9247	0.9247	93	0.9394	0.9337	0.9366	166	0.9650	0.9718	0.9684	142	0.9451	0.9451	0.9451	0.9866
0.0309	27.0	2592	0.0562	0.9082	0.9570	0.9319	93	0.9448	0.9277	0.9362	166	0.9789	0.9789	0.9789	142	0.9479	0.9526	0.9502	0.9879
0.0311	28.0	2688	0.0547	0.8804	0.8710	0.8757	93	0.8851	0.9277	0.9059	166	0.9786	0.9648	0.9716	142	0.9163	0.9277	0.9219	0.9866
0.0272	29.0	2784	0.0543	0.8544	0.9462	0.8980	93	0.9187	0.8855	0.9018	166	0.9716	0.9648	0.9682	142	0.9208	0.9277	0.9242	0.9868
0.0257	30.0	2880	0.0589	0.8660	0.9032	0.8842	93	0.8571	0.9398	0.8966	166	0.9858	0.9789	0.9823	142	0.9024	0.9451	0.9233	0.9844
0.0263	31.0	2976	0.0547	0.9167	0.9462	0.9312	93	0.9387	0.9217	0.9301	166	0.9787	0.9718	0.9753	142	0.9475	0.9451	0.9463	0.9882
0.0271	32.0	3072	0.0531	0.9082	0.9570	0.9319	93	0.9383	0.9157	0.9268	166	0.9653	0.9789	0.9720	142	0.9406	0.9476	0.9441	0.9874
0.0271	33.0	3168	0.0502	0.8878	0.9355	0.9110	93	0.9379	0.9096	0.9235	166	0.9789	0.9789	0.9789	142	0.9401	0.9401	0.9401	0.9874
0.0255	34.0	3264	0.0632	0.89	0.9570	0.9223	93	0.9451	0.9337	0.9394	166	0.9720	0.9789	0.9754	142	0.9410	0.9551	0.9480	0.9874
0.0235	35.0	3360	0.0592	0.8889	0.9462	0.9167	93	0.9394	0.9337	0.9366	166	0.9517	0.9718	0.9617	142	0.9315	0.9501	0.9407	0.9863
0.0243	36.0	3456	0.0575	0.8654	0.9677	0.9137	93	0.9560	0.9157	0.9354	166	0.9650	0.9718	0.9684	142	0.9360	0.9476	0.9418	0.9877
0.0225	37.0	3552	0.0586	0.8980	0.9462	0.9215	93	0.9042	0.9096	0.9069	166	0.9586	0.9789	0.9686	142	0.9220	0.9426	0.9322	0.9868
0.0239	38.0	3648	0.0495	0.8969	0.9355	0.9158	93	0.9277	0.9277	0.9277	166	0.9787	0.9718	0.9753	142	0.9381	0.9451	0.9416	0.9885
0.0202	39.0	3744	0.0533	0.8824	0.9677	0.9231	93	0.9437	0.9096	0.9264	166	0.9789	0.9789	0.9789	142	0.9406	0.9476	0.9441	0.9890
0.0199	40.0	3840	0.0547	0.9053	0.9247	0.9149	93	0.9277	0.9277	0.9277	166	0.9580	0.9648	0.9614	142	0.9332	0.9401	0.9366	0.9879
0.0219	41.0	3936	0.0562	0.8947	0.9140	0.9043	93	0.9172	0.9337	0.9254	166	0.9720	0.9789	0.9754	142	0.9312	0.9451	0.9381	0.9874
0.0209	42.0	4032	0.0575	0.8889	0.9462	0.9167	93	0.9437	0.9096	0.9264	166	0.9720	0.9789	0.9754	142	0.9403	0.9426	0.9415	0.9874
0.0188	43.0	4128	0.0590	0.8980	0.9462	0.9215	93	0.9273	0.9217	0.9245	166	0.9653	0.9789	0.9720	142	0.9337	0.9476	0.9406	0.9874
0.0209	44.0	4224	0.0552	0.8763	0.9140	0.8947	93	0.8830	0.9096	0.8961	166	0.9787	0.9718	0.9753	142	0.9144	0.9327	0.9235	0.9855
0.0179	45.0	4320	0.0590	0.88	0.9462	0.9119	93	0.9375	0.9036	0.9202	166	0.9720	0.9789	0.9754	142	0.9355	0.9401	0.9378	0.9871
0.0173	46.0	4416	0.0643	0.8713	0.9462	0.9072	93	0.9202	0.9036	0.9119	166	0.9716	0.9648	0.9682	142	0.9259	0.9352	0.9305	0.9863
0.0199	47.0	4512	0.0652	0.8878	0.9355	0.9110	93	0.9107	0.9217	0.9162	166	0.9648	0.9648	0.9648	142	0.9240	0.9401	0.9320	0.9855
0.0183	48.0	4608	0.0625	0.9158	0.9355	0.9255	93	0.9112	0.9277	0.9194	166	0.9716	0.9648	0.9682	142	0.9333	0.9426	0.9380	0.9868
0.0176	49.0	4704	0.0577	0.8889	0.9462	0.9167	93	0.9212	0.9157	0.9184	166	0.9650	0.9718	0.9684	142	0.9287	0.9426	0.9356	0.9885
0.0176	50.0	4800	0.0624	0.9	0.9677	0.9326	93	0.9202	0.9036	0.9119	166	0.9786	0.9648	0.9716	142	0.9355	0.9401	0.9378	0.9877
0.017	51.0	4896	0.0606	0.9062	0.9355	0.9206	93	0.9053	0.9217	0.9134	166	0.9517	0.9718	0.9617	142	0.9220	0.9426	0.9322	0.9871
0.0174	52.0	4992	0.0637	0.9255	0.9355	0.9305	93	0.9172	0.9337	0.9254	166	0.9716	0.9648	0.9682	142	0.9381	0.9451	0.9416	0.9874
0.0172	53.0	5088	0.0618	0.9149	0.9247	0.9198	93	0.8994	0.9157	0.9075	166	0.9580	0.9648	0.9614	142	0.9236	0.9352	0.9294	0.9868
0.0162	54.0	5184	0.0582	0.9175	0.9570	0.9368	93	0.8994	0.9157	0.9075	166	0.9648	0.9648	0.9648	142	0.9265	0.9426	0.9345	0.9871
0.0158	55.0	5280	0.0613	0.8980	0.9462	0.9215	93	0.9259	0.9036	0.9146	166	0.9650	0.9718	0.9684	142	0.9330	0.9377	0.9353	0.9868
0.0154	56.0	5376	0.0612	0.8980	0.9462	0.9215	93	0.9048	0.9157	0.9102	166	0.9716	0.9648	0.9682	142	0.9263	0.9401	0.9332	0.9874
0.0167	57.0	5472	0.0595	0.8627	0.9462	0.9026	93	0.9202	0.9036	0.9119	166	0.9716	0.9648	0.9682	142	0.9236	0.9352	0.9294	0.9866
0.0161	58.0	5568	0.0642	0.8544	0.9462	0.8980	93	0.9430	0.8976	0.9198	166	0.9718	0.9718	0.9718	142	0.9305	0.9352	0.9328	0.9882
0.0148	59.0	5664	0.0570	0.9062	0.9355	0.9206	93	0.9277	0.9277	0.9277	166	0.9718	0.9718	0.9718	142	0.9381	0.9451	0.9416	0.9888
0.0143	60.0	5760	0.0591	0.9167	0.9462	0.9312	93	0.9277	0.9277	0.9277	166	0.9650	0.9718	0.9684	142	0.9383	0.9476	0.9429	0.9877
0.0123	61.0	5856	0.0630	0.8842	0.9032	0.8936	93	0.9157	0.9157	0.9157	166	0.9580	0.9648	0.9614	142	0.9233	0.9302	0.9267	0.9860
0.013	62.0	5952	0.0677	0.9062	0.9355	0.9206	93	0.9212	0.9157	0.9184	166	0.9648	0.9648	0.9648	142	0.9330	0.9377	0.9353	0.9868
0.0136	63.0	6048	0.0608	0.9255	0.9355	0.9305	93	0.9053	0.9217	0.9134	166	0.9580	0.9648	0.9614	142	0.9286	0.9401	0.9343	0.9874
0.0123	64.0	6144	0.0662	0.9158	0.9355	0.9255	93	0.9217	0.9217	0.9217	166	0.9650	0.9718	0.9684	142	0.9356	0.9426	0.9391	0.9868
0.0138	65.0	6240	0.0638	0.8788	0.9355	0.9062	93	0.9152	0.9096	0.9124	166	0.9648	0.9648	0.9648	142	0.9236	0.9352	0.9294	0.9866
0.0126	66.0	6336	0.0646	0.9072	0.9462	0.9263	93	0.9152	0.9096	0.9124	166	0.9716	0.9648	0.9682	142	0.9330	0.9377	0.9353	0.9871
0.0132	67.0	6432	0.0695	0.8878	0.9355	0.9110	93	0.9091	0.9036	0.9063	166	0.9583	0.9718	0.9650	142	0.9214	0.9352	0.9282	0.9866
0.0117	68.0	6528	0.0637	0.9158	0.9355	0.9255	93	0.9212	0.9157	0.9184	166	0.9650	0.9718	0.9684	142	0.9355	0.9401	0.9378	0.9866
0.0132	69.0	6624	0.0665	0.9255	0.9355	0.9305	93	0.9222	0.9277	0.9249	166	0.9648	0.9648	0.9648	142	0.9380	0.9426	0.9403	0.9877
0.012	70.0	6720	0.0669	0.9149	0.9247	0.9198	93	0.9172	0.9337	0.9254	166	0.9650	0.9718	0.9684	142	0.9335	0.9451	0.9393	0.9868
0.0126	71.0	6816	0.0645	0.9062	0.9355	0.9206	93	0.9281	0.9337	0.9309	166	0.9716	0.9648	0.9682	142	0.9381	0.9451	0.9416	0.9882
0.0122	72.0	6912	0.0649	0.8958	0.9247	0.9101	93	0.9387	0.9217	0.9301	166	0.9720	0.9789	0.9754	142	0.9403	0.9426	0.9415	0.9871
0.0124	73.0	7008	0.0610	0.8958	0.9247	0.9101	93	0.9333	0.9277	0.9305	166	0.9720	0.9789	0.9754	142	0.9381	0.9451	0.9416	0.9882
0.0112	74.0	7104	0.0656	0.8866	0.9247	0.9053	93	0.9264	0.9096	0.9179	166	0.9718	0.9718	0.9718	142	0.9328	0.9352	0.9340	0.9866
0.011	75.0	7200	0.0644	0.8866	0.9247	0.9053	93	0.9337	0.9337	0.9337	166	0.9720	0.9789	0.9754	142	0.9360	0.9476	0.9418	0.9874
0.0095	76.0	7296	0.0660	0.8958	0.9247	0.9101	93	0.9277	0.9277	0.9277	166	0.9720	0.9789	0.9754	142	0.9358	0.9451	0.9404	0.9877
0.0103	77.0	7392	0.0669	0.8788	0.9355	0.9062	93	0.9317	0.9036	0.9174	166	0.9653	0.9789	0.9720	142	0.9307	0.9377	0.9342	0.9866
0.0102	78.0	7488	0.0640	0.8969	0.9355	0.9158	93	0.9329	0.9217	0.9273	166	0.9718	0.9718	0.9718	142	0.9380	0.9426	0.9403	0.9882
0.0105	79.0	7584	0.0625	0.9355	0.9355	0.9355	93	0.9387	0.9217	0.9301	166	0.9653	0.9789	0.9720	142	0.9475	0.9451	0.9463	0.9882
0.0099	80.0	7680	0.0648	0.8969	0.9355	0.9158	93	0.9152	0.9096	0.9124	166	0.9653	0.9789	0.9720	142	0.9286	0.9401	0.9343	0.9868
0.009	81.0	7776	0.0639	0.8958	0.9247	0.9101	93	0.9157	0.9157	0.9157	166	0.9653	0.9789	0.9720	142	0.9286	0.9401	0.9343	0.9868
0.01	82.0	7872	0.0651	0.9457	0.9355	0.9405	93	0.9217	0.9217	0.9217	166	0.9653	0.9789	0.9720	142	0.9428	0.9451	0.9440	0.9888
0.0093	83.0	7968	0.0670	0.9062	0.9355	0.9206	93	0.9268	0.9157	0.9212	166	0.9720	0.9789	0.9754	142	0.9380	0.9426	0.9403	0.9874
0.0094	84.0	8064	0.0659	0.9255	0.9355	0.9305	93	0.9212	0.9157	0.9184	166	0.9718	0.9718	0.9718	142	0.9401	0.9401	0.9401	0.9877
0.0118	85.0	8160	0.0645	0.8958	0.9247	0.9101	93	0.9268	0.9157	0.9212	166	0.9580	0.9648	0.9614	142	0.9305	0.9352	0.9328	0.9874
0.0091	86.0	8256	0.0641	0.9348	0.9247	0.9297	93	0.9277	0.9277	0.9277	166	0.9648	0.9648	0.9648	142	0.9425	0.9401	0.9413	0.9882
0.0094	87.0	8352	0.0650	0.9247	0.9247	0.9247	93	0.9167	0.9277	0.9222	166	0.9648	0.9648	0.9648	142	0.9355	0.9401	0.9378	0.9877
0.0093	88.0	8448	0.0646	0.9149	0.9247	0.9198	93	0.9333	0.9277	0.9305	166	0.9650	0.9718	0.9684	142	0.9403	0.9426	0.9415	0.9879
0.009	89.0	8544	0.0634	0.9247	0.9247	0.9247	93	0.9222	0.9277	0.9249	166	0.9650	0.9718	0.9684	142	0.9380	0.9426	0.9403	0.9874
0.0081	90.0	8640	0.0668	0.9355	0.9355	0.9355	93	0.9217	0.9217	0.9217	166	0.9720	0.9789	0.9754	142	0.9428	0.9451	0.9440	0.9885
0.0089	91.0	8736	0.0670	0.9247	0.9247	0.9247	93	0.9281	0.9337	0.9309	166	0.9718	0.9718	0.9718	142	0.9428	0.9451	0.9440	0.9877
0.0085	92.0	8832	0.0690	0.9158	0.9355	0.9255	93	0.9157	0.9157	0.9157	166	0.9718	0.9718	0.9718	142	0.9355	0.9401	0.9378	0.9874
0.0099	93.0	8928	0.0674	0.9355	0.9355	0.9355	93	0.9277	0.9277	0.9277	166	0.9718	0.9718	0.9718	142	0.9451	0.9451	0.9451	0.9882
0.0095	94.0	9024	0.0682	0.9457	0.9355	0.9405	93	0.9277	0.9277	0.9277	166	0.9718	0.9718	0.9718	142	0.9475	0.9451	0.9463	0.9882
0.0086	95.0	9120	0.0678	0.9457	0.9355	0.9405	93	0.9222	0.9277	0.9249	166	0.9718	0.9718	0.9718	142	0.9451	0.9451	0.9451	0.9882
0.0079	96.0	9216	0.0662	0.9247	0.9247	0.9247	93	0.9281	0.9337	0.9309	166	0.9718	0.9718	0.9718	142	0.9428	0.9451	0.9440	0.9879
0.0084	97.0	9312	0.0669	0.9255	0.9355	0.9305	93	0.9217	0.9217	0.9217	166	0.9718	0.9718	0.9718	142	0.9403	0.9426	0.9415	0.9879
0.0085	98.0	9408	0.0679	0.9255	0.9355	0.9305	93	0.9217	0.9217	0.9217	166	0.9718	0.9718	0.9718	142	0.9403	0.9426	0.9415	0.9874
0.0071	99.0	9504	0.0679	0.9255	0.9355	0.9305	93	0.9162	0.9217	0.9189	166	0.9718	0.9718	0.9718	142	0.9380	0.9426	0.9403	0.9877
0.0079	100.0	9600	0.0678	0.9255	0.9355	0.9305	93	0.9162	0.9217	0.9189	166	0.9718	0.9718	0.9718	142	0.9380	0.9426	0.9403	0.9877

Framework versions

Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

apwic/nerui-pt-pl5-2

nerui-pt-pl5-2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

apwic/
nerui-pt-pl5-2