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apwic/
nerui-pt-pl50-3

Name: nerui-pt-pl50-3
Availability: InStock

generated_from_trainer

indolem/indobert-base-uncased

finetune

mit

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nerui-pt-pl50-3

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: 0.0738
Location Precision: 0.9
Location Recall: 0.9419
Location F1: 0.9205
Location Number: 86
Organization Precision: 0.9480
Organization Recall: 0.9213
Organization F1: 0.9345
Organization Number: 178
Person Precision: 0.9766
Person Recall: 0.9766
Person F1: 0.9766
Person Number: 128
Overall Precision: 0.9463
Overall Recall: 0.9439
Overall F1: 0.9451
Overall Accuracy: 0.9868

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
0.8567	1.0	96	0.4086	0.0	0.0	0.0	86	0.225	0.1011	0.1395	178	0.2581	0.0625	0.1006	128	0.2321	0.0663	0.1032	0.8507
0.3561	2.0	192	0.1959	0.5	0.5814	0.5376	86	0.6272	0.5955	0.6110	178	0.8129	0.8828	0.8464	128	0.6593	0.6862	0.6725	0.9444
0.1947	3.0	288	0.1030	0.7556	0.7907	0.7727	86	0.7801	0.8371	0.8076	178	0.9265	0.9844	0.9545	128	0.8225	0.875	0.8480	0.9676
0.1377	4.0	384	0.0873	0.7609	0.8140	0.7865	86	0.7869	0.8090	0.7978	178	0.9538	0.9688	0.9612	128	0.8346	0.8622	0.8482	0.9727
0.1135	5.0	480	0.0728	0.7629	0.8605	0.8087	86	0.8441	0.8820	0.8626	178	0.9538	0.9688	0.9612	128	0.8596	0.9056	0.8820	0.9754
0.0987	6.0	576	0.0659	0.8211	0.9070	0.8619	86	0.8771	0.8820	0.8796	178	0.9688	0.9688	0.9688	128	0.8930	0.9158	0.9043	0.9789
0.0878	7.0	672	0.0588	0.8462	0.8953	0.8701	86	0.8710	0.9101	0.8901	178	0.9612	0.9688	0.9650	128	0.8941	0.9260	0.9098	0.9808
0.08	8.0	768	0.0554	0.8495	0.9186	0.8827	86	0.8624	0.9157	0.8883	178	0.984	0.9609	0.9723	128	0.8968	0.9311	0.9136	0.9814
0.0735	9.0	864	0.0520	0.8387	0.9070	0.8715	86	0.9	0.9101	0.9050	178	0.9690	0.9766	0.9728	128	0.9080	0.9311	0.9194	0.9841
0.0645	10.0	960	0.0520	0.8632	0.9535	0.9061	86	0.9050	0.9101	0.9076	178	0.9766	0.9766	0.9766	128	0.9179	0.9413	0.9295	0.9835
0.0597	11.0	1056	0.0518	0.8646	0.9651	0.9121	86	0.9205	0.9101	0.9153	178	0.9762	0.9609	0.9685	128	0.9246	0.9388	0.9316	0.9849
0.056	12.0	1152	0.0464	0.9101	0.9419	0.9257	86	0.8919	0.9270	0.9091	178	0.9690	0.9766	0.9728	128	0.9206	0.9464	0.9333	0.9852
0.0532	13.0	1248	0.0497	0.9	0.9419	0.9205	86	0.9016	0.9270	0.9141	178	0.9841	0.9688	0.9764	128	0.9273	0.9439	0.9355	0.9835
0.0512	14.0	1344	0.0478	0.9070	0.9070	0.9070	86	0.9162	0.9213	0.9188	178	0.9612	0.9688	0.9650	128	0.9289	0.9337	0.9313	0.9846
0.0459	15.0	1440	0.0487	0.8889	0.9302	0.9091	86	0.9371	0.9213	0.9292	178	0.9685	0.9609	0.9647	128	0.9362	0.9362	0.9362	0.9868
0.0462	16.0	1536	0.0502	0.8454	0.9535	0.8962	86	0.9153	0.9101	0.9127	178	0.9764	0.9688	0.9725	128	0.9177	0.9388	0.9281	0.9854
0.044	17.0	1632	0.0525	0.8778	0.9186	0.8977	86	0.9171	0.9326	0.9248	178	0.9612	0.9688	0.9650	128	0.9225	0.9413	0.9318	0.9852
0.0424	18.0	1728	0.0555	0.8804	0.9419	0.9101	86	0.9056	0.9157	0.9106	178	0.9764	0.9688	0.9725	128	0.9223	0.9388	0.9305	0.9833
0.0409	19.0	1824	0.0491	0.8876	0.9186	0.9029	86	0.8950	0.9101	0.9025	178	0.9688	0.9688	0.9688	128	0.9171	0.9311	0.9241	0.9846
0.0373	20.0	1920	0.0617	0.7767	0.9302	0.8466	86	0.8920	0.8820	0.8870	178	0.9683	0.9531	0.9606	128	0.8864	0.9158	0.9009	0.9806
0.0367	21.0	2016	0.0535	0.8351	0.9419	0.8852	86	0.9112	0.8652	0.8876	178	0.9766	0.9766	0.9766	128	0.9137	0.9184	0.9160	0.9841
0.0351	22.0	2112	0.0571	0.81	0.9419	0.8710	86	0.9306	0.9045	0.9174	178	0.9688	0.9688	0.9688	128	0.9127	0.9337	0.9231	0.9830
0.0328	23.0	2208	0.0508	0.8710	0.9419	0.9050	86	0.9415	0.9045	0.9226	178	0.9766	0.9766	0.9766	128	0.9362	0.9362	0.9362	0.9849
0.0323	24.0	2304	0.0519	0.8617	0.9419	0.9000	86	0.9222	0.9326	0.9274	178	0.9766	0.9766	0.9766	128	0.9254	0.9490	0.9370	0.9846
0.0298	25.0	2400	0.0498	0.8989	0.9302	0.9143	86	0.9257	0.9101	0.9178	178	0.9766	0.9766	0.9766	128	0.9362	0.9362	0.9362	0.9854
0.0274	26.0	2496	0.0515	0.9302	0.9302	0.9302	86	0.9081	0.9438	0.9256	178	0.9688	0.9688	0.9688	128	0.9323	0.9490	0.9406	0.9857
0.0292	27.0	2592	0.0561	0.8901	0.9419	0.9153	86	0.9171	0.9326	0.9248	178	0.9690	0.9766	0.9728	128	0.9277	0.9490	0.9382	0.9846
0.0271	28.0	2688	0.0544	0.8989	0.9302	0.9143	86	0.9121	0.9326	0.9222	178	0.9690	0.9766	0.9728	128	0.9275	0.9464	0.9369	0.9849
0.0271	29.0	2784	0.0503	0.8889	0.9302	0.9091	86	0.9022	0.9326	0.9171	178	0.9766	0.9766	0.9766	128	0.9229	0.9464	0.9345	0.9862
0.025	30.0	2880	0.0566	0.8367	0.9535	0.8913	86	0.9281	0.8708	0.8986	178	0.9766	0.9766	0.9766	128	0.9211	0.9235	0.9223	0.9849
0.0244	31.0	2976	0.0534	0.8617	0.9419	0.9000	86	0.9191	0.8933	0.9060	178	0.9766	0.9766	0.9766	128	0.9241	0.9311	0.9276	0.9857
0.0241	32.0	3072	0.0611	0.82	0.9535	0.8817	86	0.9294	0.8876	0.9080	178	0.9688	0.9688	0.9688	128	0.9146	0.9286	0.9215	0.9841
0.0229	33.0	3168	0.0556	0.8265	0.9419	0.8804	86	0.9294	0.8876	0.9080	178	0.9685	0.9609	0.9647	128	0.9165	0.9235	0.9199	0.9843
0.0227	34.0	3264	0.0545	0.8696	0.9302	0.8989	86	0.9360	0.9045	0.9200	178	0.9764	0.9688	0.9725	128	0.9335	0.9311	0.9323	0.9860
0.0223	35.0	3360	0.0530	0.8817	0.9535	0.9162	86	0.9314	0.9157	0.9235	178	0.9764	0.9688	0.9725	128	0.9342	0.9413	0.9377	0.9868
0.022	36.0	3456	0.0579	0.8438	0.9419	0.8901	86	0.9314	0.9157	0.9235	178	0.9612	0.9688	0.9650	128	0.92	0.9388	0.9293	0.9857
0.0221	37.0	3552	0.0526	0.8989	0.9302	0.9143	86	0.9322	0.9270	0.9296	178	0.9766	0.9766	0.9766	128	0.9391	0.9439	0.9415	0.9865
0.0213	38.0	3648	0.0572	0.8804	0.9419	0.9101	86	0.92	0.9045	0.9122	178	0.9690	0.9766	0.9728	128	0.9268	0.9362	0.9315	0.9857
0.0198	39.0	3744	0.0481	0.9302	0.9302	0.9302	86	0.9032	0.9438	0.9231	178	0.9688	0.9688	0.9688	128	0.93	0.9490	0.9394	0.9873
0.02	40.0	3840	0.0521	0.8791	0.9302	0.9040	86	0.9310	0.9101	0.9205	178	0.9766	0.9766	0.9766	128	0.9338	0.9362	0.9350	0.9868
0.0182	41.0	3936	0.0510	0.8723	0.9535	0.9111	86	0.9419	0.9101	0.9257	178	0.9764	0.9688	0.9725	128	0.9364	0.9388	0.9376	0.9876
0.0194	42.0	4032	0.0546	0.8791	0.9302	0.9040	86	0.9425	0.9213	0.9318	178	0.9764	0.9688	0.9725	128	0.9388	0.9388	0.9388	0.9860
0.0164	43.0	4128	0.0566	0.9	0.9419	0.9205	86	0.9419	0.9101	0.9257	178	0.9766	0.9766	0.9766	128	0.9436	0.9388	0.9412	0.9876
0.0182	44.0	4224	0.0642	0.8438	0.9419	0.8901	86	0.9345	0.8820	0.9075	178	0.9688	0.9688	0.9688	128	0.9235	0.9235	0.9235	0.9849
0.0171	45.0	4320	0.0596	0.8438	0.9419	0.8901	86	0.9422	0.9157	0.9288	178	0.9688	0.9688	0.9688	128	0.9270	0.9388	0.9328	0.9857
0.0171	46.0	4416	0.0552	0.8283	0.9535	0.8865	86	0.9405	0.8876	0.9133	178	0.9688	0.9688	0.9688	128	0.9215	0.9286	0.9250	0.9860
0.0171	47.0	4512	0.0555	0.8901	0.9419	0.9153	86	0.9375	0.9270	0.9322	178	0.984	0.9609	0.9723	128	0.9413	0.9413	0.9413	0.9879
0.0143	48.0	4608	0.0627	0.8710	0.9419	0.9050	86	0.9425	0.9213	0.9318	178	0.9762	0.9609	0.9685	128	0.9364	0.9388	0.9376	0.9868
0.016	49.0	4704	0.0568	0.8901	0.9419	0.9153	86	0.9486	0.9326	0.9405	178	0.9690	0.9766	0.9728	128	0.9418	0.9490	0.9454	0.9870
0.0133	50.0	4800	0.0609	0.8804	0.9419	0.9101	86	0.9310	0.9101	0.9205	178	0.9690	0.9766	0.9728	128	0.9316	0.9388	0.9352	0.9860
0.0149	51.0	4896	0.0576	0.8696	0.9302	0.8989	86	0.9419	0.9101	0.9257	178	0.9690	0.9766	0.9728	128	0.9338	0.9362	0.9350	0.9860
0.0146	52.0	4992	0.0545	0.9	0.9419	0.9205	86	0.9492	0.9438	0.9465	178	0.9690	0.9766	0.9728	128	0.9444	0.9541	0.9492	0.9879
0.0149	53.0	5088	0.0607	0.8989	0.9302	0.9143	86	0.9389	0.9494	0.9441	178	0.9609	0.9609	0.9609	128	0.9370	0.9490	0.9430	0.9868
0.0131	54.0	5184	0.0642	0.8901	0.9419	0.9153	86	0.9535	0.9213	0.9371	178	0.9690	0.9766	0.9728	128	0.9439	0.9439	0.9439	0.9862
0.013	55.0	5280	0.0613	0.8587	0.9186	0.8876	86	0.9364	0.9101	0.9231	178	0.9766	0.9766	0.9766	128	0.9313	0.9337	0.9325	0.9854
0.0138	56.0	5376	0.0549	0.8989	0.9302	0.9143	86	0.9270	0.9270	0.9270	178	0.9764	0.9688	0.9725	128	0.9365	0.9413	0.9389	0.9857
0.013	57.0	5472	0.0631	0.8889	0.9302	0.9091	86	0.9371	0.9213	0.9292	178	0.9688	0.9688	0.9688	128	0.9364	0.9388	0.9376	0.9860
0.0122	58.0	5568	0.0628	0.8913	0.9535	0.9213	86	0.9477	0.9157	0.9314	178	0.9690	0.9766	0.9728	128	0.9415	0.9439	0.9427	0.9870
0.012	59.0	5664	0.0651	0.9205	0.9419	0.9310	86	0.9432	0.9326	0.9379	178	0.9688	0.9688	0.9688	128	0.9464	0.9464	0.9464	0.9868
0.0122	60.0	5760	0.0651	0.8737	0.9651	0.9171	86	0.9464	0.8933	0.9191	178	0.9688	0.9688	0.9688	128	0.9361	0.9337	0.9349	0.9857
0.0115	61.0	5856	0.0647	0.9	0.9419	0.9205	86	0.9492	0.9438	0.9465	178	0.9690	0.9766	0.9728	128	0.9444	0.9541	0.9492	0.9876
0.0121	62.0	5952	0.0635	0.9101	0.9419	0.9257	86	0.9371	0.9213	0.9292	178	0.9690	0.9766	0.9728	128	0.9415	0.9439	0.9427	0.9865
0.011	63.0	6048	0.0638	0.9091	0.9302	0.9195	86	0.9486	0.9326	0.9405	178	0.9690	0.9766	0.9728	128	0.9464	0.9464	0.9464	0.9868
0.0113	64.0	6144	0.0583	0.8913	0.9535	0.9213	86	0.9368	0.9157	0.9261	178	0.9764	0.9688	0.9725	128	0.9389	0.9413	0.9401	0.9868
0.0107	65.0	6240	0.0674	0.9	0.9419	0.9205	86	0.9375	0.9270	0.9322	178	0.9688	0.9688	0.9688	128	0.9391	0.9439	0.9415	0.9857
0.0106	66.0	6336	0.0687	0.9011	0.9535	0.9266	86	0.9474	0.9101	0.9284	178	0.9690	0.9766	0.9728	128	0.9437	0.9413	0.9425	0.9857
0.0102	67.0	6432	0.0663	0.8901	0.9419	0.9153	86	0.9422	0.9157	0.9288	178	0.9766	0.9766	0.9766	128	0.9413	0.9413	0.9413	0.9860
0.0099	68.0	6528	0.0665	0.8989	0.9302	0.9143	86	0.9540	0.9326	0.9432	178	0.9690	0.9766	0.9728	128	0.9464	0.9464	0.9464	0.9865
0.0108	69.0	6624	0.0600	0.9195	0.9302	0.9249	86	0.9432	0.9326	0.9379	178	0.9766	0.9766	0.9766	128	0.9488	0.9464	0.9476	0.9881
0.0096	70.0	6720	0.0623	0.9101	0.9419	0.9257	86	0.9330	0.9382	0.9356	178	0.9685	0.9609	0.9647	128	0.9392	0.9464	0.9428	0.9876
0.0105	71.0	6816	0.0666	0.9011	0.9535	0.9266	86	0.9425	0.9213	0.9318	178	0.9690	0.9766	0.9728	128	0.9416	0.9464	0.9440	0.9868
0.0088	72.0	6912	0.0666	0.9111	0.9535	0.9318	86	0.9353	0.8933	0.9138	178	0.9766	0.9766	0.9766	128	0.9433	0.9337	0.9385	0.9868
0.0104	73.0	7008	0.0699	0.8989	0.9302	0.9143	86	0.9360	0.9045	0.9200	178	0.9690	0.9766	0.9728	128	0.9385	0.9337	0.9361	0.9857
0.0087	74.0	7104	0.0669	0.8989	0.9302	0.9143	86	0.9371	0.9213	0.9292	178	0.9690	0.9766	0.9728	128	0.9389	0.9413	0.9401	0.9865
0.0093	75.0	7200	0.0710	0.8989	0.9302	0.9143	86	0.9368	0.9157	0.9261	178	0.9690	0.9766	0.9728	128	0.9388	0.9388	0.9388	0.9862
0.0098	76.0	7296	0.0709	0.8989	0.9302	0.9143	86	0.9364	0.9101	0.9231	178	0.9690	0.9766	0.9728	128	0.9386	0.9362	0.9374	0.9862
0.0091	77.0	7392	0.0709	0.9011	0.9535	0.9266	86	0.9532	0.9157	0.9341	178	0.9690	0.9766	0.9728	128	0.9463	0.9439	0.9451	0.9868
0.0082	78.0	7488	0.0711	0.8989	0.9302	0.9143	86	0.9425	0.9213	0.9318	178	0.9766	0.9766	0.9766	128	0.9437	0.9413	0.9425	0.9868
0.0099	79.0	7584	0.0680	0.8989	0.9302	0.9143	86	0.9379	0.9326	0.9352	178	0.9690	0.9766	0.9728	128	0.9392	0.9464	0.9428	0.9868
0.008	80.0	7680	0.0717	0.9101	0.9419	0.9257	86	0.9368	0.9157	0.9261	178	0.9690	0.9766	0.9728	128	0.9413	0.9413	0.9413	0.9865
0.0094	81.0	7776	0.0729	0.9111	0.9535	0.9318	86	0.9483	0.9270	0.9375	178	0.9690	0.9766	0.9728	128	0.9466	0.9490	0.9478	0.9870
0.0081	82.0	7872	0.0714	0.8989	0.9302	0.9143	86	0.9314	0.9157	0.9235	178	0.9690	0.9766	0.9728	128	0.9364	0.9388	0.9376	0.9860
0.0087	83.0	7968	0.0696	0.9011	0.9535	0.9266	86	0.9368	0.9157	0.9261	178	0.9766	0.9766	0.9766	128	0.9415	0.9439	0.9427	0.9868
0.0072	84.0	8064	0.0713	0.9121	0.9651	0.9379	86	0.9425	0.9213	0.9318	178	0.9688	0.9688	0.9688	128	0.9440	0.9464	0.9452	0.9870
0.0072	85.0	8160	0.0726	0.9011	0.9535	0.9266	86	0.9422	0.9157	0.9288	178	0.9764	0.9688	0.9725	128	0.9437	0.9413	0.9425	0.9862
0.0069	86.0	8256	0.0700	0.9011	0.9535	0.9266	86	0.9310	0.9101	0.9205	178	0.9612	0.9688	0.9650	128	0.9340	0.9388	0.9364	0.9860
0.0075	87.0	8352	0.0742	0.9101	0.9419	0.9257	86	0.9310	0.9101	0.9205	178	0.9612	0.9688	0.9650	128	0.9362	0.9362	0.9362	0.9857
0.0081	88.0	8448	0.0733	0.8989	0.9302	0.9143	86	0.9375	0.9270	0.9322	178	0.9690	0.9766	0.9728	128	0.9391	0.9439	0.9415	0.9865
0.0076	89.0	8544	0.0715	0.9101	0.9419	0.9257	86	0.9371	0.9213	0.9292	178	0.9688	0.9688	0.9688	128	0.9413	0.9413	0.9413	0.9865
0.007	90.0	8640	0.0731	0.9101	0.9419	0.9257	86	0.9429	0.9270	0.9348	178	0.9688	0.9688	0.9688	128	0.9439	0.9439	0.9439	0.9868
0.0067	91.0	8736	0.0735	0.9	0.9419	0.9205	86	0.9425	0.9213	0.9318	178	0.9688	0.9688	0.9688	128	0.9413	0.9413	0.9413	0.9865
0.0063	92.0	8832	0.0729	0.8889	0.9302	0.9091	86	0.9371	0.9213	0.9292	178	0.9688	0.9688	0.9688	128	0.9364	0.9388	0.9376	0.9862
0.0071	93.0	8928	0.0748	0.9	0.9419	0.9205	86	0.9425	0.9213	0.9318	178	0.9688	0.9688	0.9688	128	0.9413	0.9413	0.9413	0.9865
0.0069	94.0	9024	0.0724	0.8889	0.9302	0.9091	86	0.9425	0.9213	0.9318	178	0.9688	0.9688	0.9688	128	0.9388	0.9388	0.9388	0.9865
0.0079	95.0	9120	0.0744	0.9	0.9419	0.9205	86	0.9535	0.9213	0.9371	178	0.9766	0.9766	0.9766	128	0.9487	0.9439	0.9463	0.9870
0.0066	96.0	9216	0.0743	0.9	0.9419	0.9205	86	0.9480	0.9213	0.9345	178	0.9766	0.9766	0.9766	128	0.9463	0.9439	0.9451	0.9868
0.0077	97.0	9312	0.0732	0.9	0.9419	0.9205	86	0.9480	0.9213	0.9345	178	0.9766	0.9766	0.9766	128	0.9463	0.9439	0.9451	0.9868
0.0063	98.0	9408	0.0736	0.9	0.9419	0.9205	86	0.9480	0.9213	0.9345	178	0.9766	0.9766	0.9766	128	0.9463	0.9439	0.9451	0.9868
0.0068	99.0	9504	0.0737	0.9	0.9419	0.9205	86	0.9480	0.9213	0.9345	178	0.9766	0.9766	0.9766	128	0.9463	0.9439	0.9451	0.9868
0.0077	100.0	9600	0.0738	0.9	0.9419	0.9205	86	0.9480	0.9213	0.9345	178	0.9766	0.9766	0.9766	128	0.9463	0.9439	0.9451	0.9868

Framework versions

Transformers 4.40.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

apwic/nerui-pt-pl50-3

nerui-pt-pl50-3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

apwic/
nerui-pt-pl50-3