nerui-seq_bn-rf64-4

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: 0.0385
• Location Precision: 0.9238
• Location Recall: 0.9417
• Location F1: 0.9327
• Location Number: 103
• Organization Precision: 0.9128
• Organization Recall: 0.9181
• Organization F1: 0.9155
• Organization Number: 171
• Person Precision: 0.9771
• Person Recall: 0.9771
• Person F1: 0.9771
• Person Number: 131
• Overall Precision: 0.9363
• Overall Recall: 0.9432
• Overall F1: 0.9397
• 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
1.0711	1.0	96	0.6462	0.0	0.0	0.0	103	0.0	0.0	0.0	171	0.0	0.0	0.0	131	0.0	0.0	0.0	0.8373
0.5955	2.0	192	0.4464	0.0	0.0	0.0	103	0.28	0.0409	0.0714	171	0.3158	0.0916	0.1420	131	0.2969	0.0469	0.0810	0.8453
0.4337	3.0	288	0.3274	0.3889	0.1359	0.2014	103	0.3756	0.4503	0.4096	171	0.3383	0.5191	0.4096	131	0.3597	0.3926	0.3754	0.8934
0.3506	4.0	384	0.2830	0.4737	0.3495	0.4022	103	0.4416	0.5965	0.5075	171	0.3971	0.6183	0.4836	131	0.4286	0.5407	0.4782	0.9152
0.3082	5.0	480	0.2468	0.4810	0.3689	0.4176	103	0.5219	0.6959	0.5965	171	0.5114	0.6870	0.5863	131	0.5114	0.6099	0.5563	0.9310
0.2709	6.0	576	0.2129	0.4948	0.4660	0.4800	103	0.5708	0.7544	0.6499	171	0.5906	0.7710	0.6689	131	0.5628	0.6864	0.6185	0.9420
0.2357	7.0	672	0.1773	0.5354	0.5146	0.5248	103	0.6415	0.7953	0.7102	171	0.75	0.8702	0.8057	131	0.6544	0.7481	0.6982	0.9544
0.1989	8.0	768	0.1463	0.68	0.6602	0.6700	103	0.7513	0.8304	0.7889	171	0.8380	0.9084	0.8718	131	0.7633	0.8123	0.7871	0.9658
0.1699	9.0	864	0.1226	0.7143	0.7282	0.7212	103	0.7778	0.8596	0.8167	171	0.8652	0.9313	0.8971	131	0.7908	0.8494	0.8190	0.9696
0.1429	10.0	960	0.1061	0.7838	0.8447	0.8131	103	0.8232	0.8713	0.8466	171	0.9051	0.9466	0.9254	131	0.8392	0.8889	0.8633	0.9743
0.1286	11.0	1056	0.0951	0.8165	0.8641	0.8396	103	0.8034	0.8363	0.8195	171	0.9124	0.9542	0.9328	131	0.8420	0.8815	0.8613	0.9751
0.1195	12.0	1152	0.0885	0.7946	0.8641	0.8279	103	0.8066	0.8538	0.8295	171	0.9130	0.9618	0.9368	131	0.8376	0.8914	0.8636	0.9749
0.1123	13.0	1248	0.0820	0.8182	0.8738	0.8451	103	0.8278	0.8713	0.8490	171	0.9130	0.9618	0.9368	131	0.8528	0.9012	0.8764	0.9771
0.1048	14.0	1344	0.0789	0.8349	0.8835	0.8585	103	0.8266	0.8363	0.8314	171	0.9333	0.9618	0.9474	131	0.8633	0.8889	0.8759	0.9782
0.0992	15.0	1440	0.0732	0.8585	0.8835	0.8708	103	0.8324	0.8713	0.8514	171	0.9197	0.9618	0.9403	131	0.8673	0.9037	0.8851	0.9776
0.0947	16.0	1536	0.0708	0.8505	0.8835	0.8667	103	0.8054	0.8713	0.8371	171	0.9478	0.9695	0.9585	131	0.8615	0.9062	0.8833	0.9779
0.0925	17.0	1632	0.0685	0.9010	0.8835	0.8922	103	0.8362	0.8655	0.8506	171	0.9265	0.9618	0.9438	131	0.8816	0.9012	0.8913	0.9790
0.0882	18.0	1728	0.0656	0.8692	0.9029	0.8857	103	0.8605	0.8655	0.8630	171	0.9478	0.9695	0.9585	131	0.8910	0.9086	0.8998	0.9796
0.0837	19.0	1824	0.0655	0.8692	0.9029	0.8857	103	0.8497	0.8596	0.8547	171	0.9338	0.9695	0.9513	131	0.8822	0.9062	0.8940	0.9787
0.0834	20.0	1920	0.0630	0.8785	0.9126	0.8952	103	0.8427	0.8772	0.8596	171	0.9478	0.9695	0.9585	131	0.8854	0.9160	0.9005	0.9796
0.0783	21.0	2016	0.0605	0.8704	0.9126	0.8910	103	0.8671	0.8772	0.8721	171	0.9478	0.9695	0.9585	131	0.8940	0.9160	0.9049	0.9807
0.0769	22.0	2112	0.0590	0.9048	0.9223	0.9135	103	0.8619	0.9123	0.8864	171	0.9338	0.9695	0.9513	131	0.8957	0.9333	0.9141	0.9812
0.0754	23.0	2208	0.0569	0.9048	0.9223	0.9135	103	0.8693	0.8947	0.8818	171	0.9407	0.9695	0.9549	131	0.9014	0.9259	0.9135	0.9820
0.0742	24.0	2304	0.0588	0.8716	0.9223	0.8962	103	0.8655	0.8655	0.8655	171	0.9338	0.9695	0.9513	131	0.8894	0.9136	0.9013	0.9798
0.0726	25.0	2400	0.0568	0.9048	0.9223	0.9135	103	0.8728	0.8830	0.8779	171	0.9338	0.9695	0.9513	131	0.9010	0.9210	0.9109	0.9809
0.0693	26.0	2496	0.0547	0.9048	0.9223	0.9135	103	0.8882	0.8830	0.8856	171	0.9270	0.9695	0.9478	131	0.9053	0.9210	0.9131	0.9826
0.07	27.0	2592	0.0528	0.9126	0.9126	0.9126	103	0.8619	0.9123	0.8864	171	0.9407	0.9695	0.9549	131	0.8998	0.9309	0.9150	0.9832
0.069	28.0	2688	0.0520	0.9135	0.9223	0.9179	103	0.8771	0.9181	0.8971	171	0.9407	0.9695	0.9549	131	0.9067	0.9358	0.9210	0.9840
0.0652	29.0	2784	0.0530	0.9223	0.9223	0.9223	103	0.8588	0.8889	0.8736	171	0.9478	0.9695	0.9585	131	0.9034	0.9235	0.9133	0.9834
0.0638	30.0	2880	0.0522	0.9223	0.9223	0.9223	103	0.875	0.9006	0.8876	171	0.9338	0.9695	0.9513	131	0.9060	0.9284	0.9171	0.9837
0.0642	31.0	2976	0.0512	0.9223	0.9223	0.9223	103	0.8693	0.8947	0.8818	171	0.9407	0.9695	0.9549	131	0.9058	0.9259	0.9158	0.9832
0.0613	32.0	3072	0.0493	0.9143	0.9320	0.9231	103	0.9023	0.9181	0.9101	171	0.9407	0.9695	0.9549	131	0.9179	0.9383	0.9280	0.9848
0.0592	33.0	3168	0.0479	0.9135	0.9223	0.9179	103	0.9070	0.9123	0.9096	171	0.9478	0.9695	0.9585	131	0.9220	0.9333	0.9276	0.9856
0.0578	34.0	3264	0.0478	0.9216	0.9126	0.9171	103	0.9017	0.9123	0.9070	171	0.9407	0.9695	0.9549	131	0.9195	0.9309	0.9252	0.9845
0.0586	35.0	3360	0.0482	0.9126	0.9126	0.9126	103	0.8902	0.9006	0.8953	171	0.9407	0.9695	0.9549	131	0.9124	0.9259	0.9191	0.9837
0.0588	36.0	3456	0.0460	0.9126	0.9126	0.9126	103	0.9064	0.9064	0.9064	171	0.9407	0.9695	0.9549	131	0.9193	0.9284	0.9238	0.9848
0.0568	37.0	3552	0.0462	0.92	0.8932	0.9064	103	0.8820	0.9181	0.8997	171	0.9478	0.9695	0.9585	131	0.9126	0.9284	0.9204	0.9845
0.0554	38.0	3648	0.0465	0.9057	0.9320	0.9187	103	0.8947	0.8947	0.8947	171	0.9478	0.9695	0.9585	131	0.9148	0.9284	0.9216	0.9851
0.0529	39.0	3744	0.0439	0.9057	0.9320	0.9187	103	0.9017	0.9123	0.9070	171	0.9478	0.9695	0.9585	131	0.9177	0.9358	0.9267	0.9856
0.0528	40.0	3840	0.0452	0.9126	0.9126	0.9126	103	0.9118	0.9064	0.9091	171	0.9478	0.9695	0.9585	131	0.9238	0.9284	0.9261	0.9851
0.0524	41.0	3936	0.0431	0.9216	0.9126	0.9171	103	0.8977	0.9240	0.9107	171	0.9478	0.9695	0.9585	131	0.9199	0.9358	0.9278	0.9859
0.0529	42.0	4032	0.0419	0.9216	0.9126	0.9171	103	0.8827	0.9240	0.9029	171	0.9478	0.9695	0.9585	131	0.9133	0.9358	0.9244	0.9862
0.0513	43.0	4128	0.0432	0.9135	0.9223	0.9179	103	0.8902	0.9006	0.8953	171	0.9478	0.9695	0.9585	131	0.9148	0.9284	0.9216	0.9854
0.0488	44.0	4224	0.0448	0.9048	0.9223	0.9135	103	0.8830	0.8830	0.8830	171	0.9478	0.9695	0.9585	131	0.9098	0.9210	0.9153	0.9843
0.0498	45.0	4320	0.0427	0.9038	0.9126	0.9082	103	0.8895	0.8947	0.8921	171	0.9549	0.9695	0.9621	131	0.9144	0.9235	0.9189	0.9848
0.0487	46.0	4416	0.0428	0.9231	0.9320	0.9275	103	0.9064	0.9064	0.9064	171	0.9478	0.9695	0.9585	131	0.9242	0.9333	0.9287	0.9859
0.0478	47.0	4512	0.0410	0.9216	0.9126	0.9171	103	0.8736	0.9298	0.9008	171	0.9478	0.9695	0.9585	131	0.9091	0.9383	0.9235	0.9865
0.0483	48.0	4608	0.0430	0.9048	0.9223	0.9135	103	0.8779	0.8830	0.8805	171	0.9549	0.9695	0.9621	131	0.9098	0.9210	0.9153	0.9854
0.0449	49.0	4704	0.0408	0.9238	0.9417	0.9327	103	0.9023	0.9181	0.9101	171	0.9478	0.9695	0.9585	131	0.9225	0.9407	0.9315	0.9870
0.0444	50.0	4800	0.0418	0.8952	0.9126	0.9038	103	0.9006	0.9006	0.9006	171	0.9549	0.9695	0.9621	131	0.9169	0.9259	0.9214	0.9859
0.0466	51.0	4896	0.0413	0.9238	0.9417	0.9327	103	0.9112	0.9006	0.9059	171	0.9478	0.9695	0.9585	131	0.9265	0.9333	0.9299	0.9862
0.0444	52.0	4992	0.0413	0.9216	0.9126	0.9171	103	0.8857	0.9064	0.8960	171	0.9621	0.9695	0.9658	131	0.9193	0.9284	0.9238	0.9865
0.044	53.0	5088	0.0415	0.9231	0.9320	0.9275	103	0.9059	0.9006	0.9032	171	0.9478	0.9695	0.9585	131	0.9240	0.9309	0.9274	0.9859
0.0432	54.0	5184	0.0404	0.9307	0.9126	0.9216	103	0.8743	0.9357	0.9040	171	0.9549	0.9695	0.9621	131	0.9137	0.9407	0.9270	0.9865
0.0447	55.0	5280	0.0416	0.9231	0.9320	0.9275	103	0.9006	0.9006	0.9006	171	0.9549	0.9695	0.9621	131	0.9240	0.9309	0.9274	0.9865
0.0437	56.0	5376	0.0413	0.9412	0.9320	0.9366	103	0.9123	0.9123	0.9123	171	0.9549	0.9695	0.9621	131	0.9335	0.9358	0.9346	0.9867
0.0428	57.0	5472	0.0402	0.9320	0.9320	0.9320	103	0.9080	0.9240	0.9159	171	0.9549	0.9695	0.9621	131	0.9293	0.9407	0.9350	0.9873
0.042	58.0	5568	0.0409	0.9320	0.9320	0.9320	103	0.9118	0.9064	0.9091	171	0.9621	0.9695	0.9658	131	0.9333	0.9333	0.9333	0.9873
0.0397	59.0	5664	0.0393	0.9406	0.9223	0.9314	103	0.8920	0.9181	0.9049	171	0.9407	0.9695	0.9549	131	0.9199	0.9358	0.9278	0.9870
0.041	60.0	5760	0.0401	0.9320	0.9320	0.9320	103	0.9231	0.9123	0.9176	171	0.9621	0.9695	0.9658	131	0.9381	0.9358	0.9370	0.9876
0.0424	61.0	5856	0.0409	0.9412	0.9320	0.9366	103	0.9226	0.9064	0.9145	171	0.9549	0.9695	0.9621	131	0.9380	0.9333	0.9356	0.9873
0.0423	62.0	5952	0.0406	0.9151	0.9417	0.9282	103	0.9053	0.8947	0.9000	171	0.9621	0.9695	0.9658	131	0.9263	0.9309	0.9286	0.9873
0.0401	63.0	6048	0.0393	0.9245	0.9515	0.9378	103	0.9235	0.9181	0.9208	171	0.9621	0.9695	0.9658	131	0.9363	0.9432	0.9397	0.9878
0.0382	64.0	6144	0.0397	0.9417	0.9417	0.9417	103	0.9286	0.9123	0.9204	171	0.9621	0.9695	0.9658	131	0.9429	0.9383	0.9406	0.9881
0.0397	65.0	6240	0.0386	0.9412	0.9320	0.9366	103	0.9138	0.9298	0.9217	171	0.9697	0.9771	0.9734	131	0.9387	0.9457	0.9422	0.9881
0.0397	66.0	6336	0.0405	0.9238	0.9417	0.9327	103	0.9281	0.9064	0.9172	171	0.9621	0.9695	0.9658	131	0.9381	0.9358	0.9370	0.9873
0.0387	67.0	6432	0.0412	0.9231	0.9320	0.9275	103	0.9053	0.8947	0.9000	171	0.9621	0.9695	0.9658	131	0.9284	0.9284	0.9284	0.9865
0.0398	68.0	6528	0.0391	0.9320	0.9320	0.9320	103	0.9133	0.9240	0.9186	171	0.9695	0.9695	0.9695	131	0.9361	0.9407	0.9384	0.9876
0.0381	69.0	6624	0.0395	0.9320	0.9320	0.9320	103	0.9181	0.9181	0.9181	171	0.9621	0.9695	0.9658	131	0.9360	0.9383	0.9371	0.9876
0.0359	70.0	6720	0.0392	0.9320	0.9320	0.9320	103	0.9128	0.9181	0.9155	171	0.9695	0.9695	0.9695	131	0.9360	0.9383	0.9371	0.9873
0.0368	71.0	6816	0.0387	0.9406	0.9223	0.9314	103	0.8889	0.9357	0.9117	171	0.9695	0.9695	0.9695	131	0.9272	0.9432	0.9351	0.9867
0.0372	72.0	6912	0.0409	0.9412	0.9320	0.9366	103	0.9123	0.9123	0.9123	171	0.9621	0.9695	0.9658	131	0.9358	0.9358	0.9358	0.9881
0.0362	73.0	7008	0.0389	0.9314	0.9223	0.9268	103	0.8876	0.9240	0.9054	171	0.9695	0.9695	0.9695	131	0.9246	0.9383	0.9314	0.9862
0.0386	74.0	7104	0.0395	0.9314	0.9223	0.9268	103	0.8876	0.9240	0.9054	171	0.9695	0.9695	0.9695	131	0.9246	0.9383	0.9314	0.9862
0.0366	75.0	7200	0.0399	0.9412	0.9320	0.9366	103	0.9235	0.9181	0.9208	171	0.9621	0.9695	0.9658	131	0.9406	0.9383	0.9394	0.9881
0.0363	76.0	7296	0.0393	0.9314	0.9223	0.9268	103	0.9133	0.9240	0.9186	171	0.9697	0.9771	0.9734	131	0.9361	0.9407	0.9384	0.9878
0.0355	77.0	7392	0.0390	0.9406	0.9223	0.9314	103	0.9128	0.9181	0.9155	171	0.9621	0.9695	0.9658	131	0.9358	0.9358	0.9358	0.9878
0.0367	78.0	7488	0.0390	0.9406	0.9223	0.9314	103	0.9075	0.9181	0.9128	171	0.9771	0.9771	0.9771	131	0.9383	0.9383	0.9383	0.9876
0.0342	79.0	7584	0.0393	0.9406	0.9223	0.9314	103	0.9128	0.9181	0.9155	171	0.9621	0.9695	0.9658	131	0.9358	0.9358	0.9358	0.9876
0.0344	80.0	7680	0.0400	0.9314	0.9223	0.9268	103	0.9128	0.9181	0.9155	171	0.9621	0.9695	0.9658	131	0.9335	0.9358	0.9346	0.9873
0.0346	81.0	7776	0.0388	0.9314	0.9223	0.9268	103	0.8977	0.9240	0.9107	171	0.9621	0.9695	0.9658	131	0.9268	0.9383	0.9325	0.9867
0.0342	82.0	7872	0.0391	0.9314	0.9223	0.9268	103	0.8977	0.9240	0.9107	171	0.9621	0.9695	0.9658	131	0.9268	0.9383	0.9325	0.9870
0.0343	83.0	7968	0.0387	0.9406	0.9223	0.9314	103	0.9075	0.9181	0.9128	171	0.9621	0.9695	0.9658	131	0.9335	0.9358	0.9346	0.9873
0.0347	84.0	8064	0.0384	0.9223	0.9223	0.9223	103	0.8920	0.9181	0.9049	171	0.9695	0.9695	0.9695	131	0.9244	0.9358	0.9301	0.9862
0.035	85.0	8160	0.0396	0.9314	0.9223	0.9268	103	0.9123	0.9123	0.9123	171	0.9621	0.9695	0.9658	131	0.9333	0.9333	0.9333	0.9876
0.0315	86.0	8256	0.0385	0.9223	0.9223	0.9223	103	0.9023	0.9181	0.9101	171	0.9771	0.9771	0.9771	131	0.9314	0.9383	0.9348	0.9873
0.0344	87.0	8352	0.0387	0.9406	0.9223	0.9314	103	0.9128	0.9181	0.9155	171	0.9621	0.9695	0.9658	131	0.9358	0.9358	0.9358	0.9876
0.035	88.0	8448	0.0385	0.9412	0.9320	0.9366	103	0.9191	0.9298	0.9244	171	0.9771	0.9771	0.9771	131	0.9433	0.9457	0.9445	0.9887
0.0358	89.0	8544	0.0384	0.9223	0.9223	0.9223	103	0.8971	0.9181	0.9075	171	0.9771	0.9771	0.9771	131	0.9291	0.9383	0.9337	0.9870
0.0345	90.0	8640	0.0384	0.9223	0.9223	0.9223	103	0.8971	0.9181	0.9075	171	0.9771	0.9771	0.9771	131	0.9291	0.9383	0.9337	0.9870
0.0336	91.0	8736	0.0384	0.9238	0.9417	0.9327	103	0.9070	0.9123	0.9096	171	0.9697	0.9771	0.9734	131	0.9315	0.9407	0.9361	0.9876
0.0334	92.0	8832	0.0385	0.9151	0.9417	0.9282	103	0.9176	0.9123	0.9150	171	0.9771	0.9771	0.9771	131	0.9361	0.9407	0.9384	0.9878
0.0328	93.0	8928	0.0383	0.9406	0.9223	0.9314	103	0.9080	0.9240	0.9159	171	0.9771	0.9771	0.9771	131	0.9384	0.9407	0.9396	0.9878
0.0332	94.0	9024	0.0387	0.9327	0.9417	0.9372	103	0.9181	0.9181	0.9181	171	0.9621	0.9695	0.9658	131	0.9361	0.9407	0.9384	0.9881
0.0331	95.0	9120	0.0386	0.9238	0.9417	0.9327	103	0.9181	0.9181	0.9181	171	0.9771	0.9771	0.9771	131	0.9386	0.9432	0.9409	0.9884
0.0322	96.0	9216	0.0387	0.9327	0.9417	0.9372	103	0.9181	0.9181	0.9181	171	0.9697	0.9771	0.9734	131	0.9386	0.9432	0.9409	0.9881
0.0341	97.0	9312	0.0387	0.9238	0.9417	0.9327	103	0.9070	0.9123	0.9096	171	0.9697	0.9771	0.9734	131	0.9315	0.9407	0.9361	0.9876
0.0331	98.0	9408	0.0387	0.9238	0.9417	0.9327	103	0.9070	0.9123	0.9096	171	0.9697	0.9771	0.9734	131	0.9315	0.9407	0.9361	0.9878
0.0319	99.0	9504	0.0386	0.9238	0.9417	0.9327	103	0.9070	0.9123	0.9096	171	0.9697	0.9771	0.9734	131	0.9315	0.9407	0.9361	0.9876
0.0329	100.0	9600	0.0385	0.9238	0.9417	0.9327	103	0.9128	0.9181	0.9155	171	0.9771	0.9771	0.9771	131	0.9363	0.9432	0.9397	0.9878

Framework versions

• Transformers 4.40.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1