nerui-seq_bn-rf64-1

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: 0.0340
• Location Precision: 0.9160
• Location Recall: 0.9397
• Location F1: 0.9277
• Location Number: 116
• Organization Precision: 0.9371
• Organization Recall: 0.9430
• Organization F1: 0.9401
• Organization Number: 158
• Person Precision: 0.9685
• Person Recall: 0.9919
• Person F1: 0.9801
• Person Number: 124
• Overall Precision: 0.9407
• Overall Recall: 0.9573
• Overall F1: 0.9489
• Overall Accuracy: 0.9882

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
1.0547	1.0	96	0.6439	0.0	0.0	0.0	116	0.0	0.0	0.0	158	0.0	0.0	0.0	124	0.0	0.0	0.0	0.8394
0.5973	2.0	192	0.4455	0.0	0.0	0.0	116	0.3636	0.0506	0.0889	158	0.3448	0.0806	0.1307	124	0.3396	0.0452	0.0798	0.8457
0.4304	3.0	288	0.3282	0.3793	0.1897	0.2529	116	0.3692	0.5	0.4247	158	0.3520	0.5565	0.4313	124	0.3632	0.4271	0.3926	0.8973
0.3462	4.0	384	0.2760	0.4767	0.3534	0.4059	116	0.4635	0.5633	0.5086	158	0.3865	0.6452	0.4834	124	0.4330	0.5276	0.4757	0.9171
0.3083	5.0	480	0.2443	0.4891	0.3879	0.4327	116	0.4848	0.7089	0.5758	158	0.5269	0.7097	0.6048	124	0.5	0.6156	0.5518	0.9306
0.2762	6.0	576	0.2112	0.5299	0.5345	0.5322	116	0.5476	0.7278	0.625	158	0.6196	0.8145	0.7038	124	0.5673	0.6985	0.6261	0.9448
0.2372	7.0	672	0.1746	0.56	0.6034	0.5809	116	0.6205	0.7658	0.6856	158	0.7415	0.8790	0.8044	124	0.6424	0.7538	0.6936	0.9555
0.2032	8.0	768	0.1440	0.6423	0.6810	0.6611	116	0.6978	0.8038	0.7471	158	0.7832	0.9032	0.8390	124	0.7098	0.7990	0.7518	0.9649
0.1698	9.0	864	0.1209	0.7016	0.75	0.725	116	0.7374	0.8354	0.7834	158	0.8156	0.9274	0.8679	124	0.7523	0.8392	0.7933	0.9679
0.1454	10.0	960	0.1023	0.7742	0.8276	0.8000	116	0.7882	0.8481	0.8171	158	0.9023	0.9677	0.9339	124	0.8197	0.8794	0.8485	0.9739
0.1335	11.0	1056	0.0897	0.8	0.8621	0.8299	116	0.8171	0.8481	0.8323	158	0.9030	0.9758	0.9380	124	0.8392	0.8920	0.8648	0.9756
0.1188	12.0	1152	0.0829	0.7891	0.8707	0.8279	116	0.8193	0.8608	0.8395	158	0.9037	0.9839	0.9421	124	0.8368	0.9020	0.8682	0.9753
0.1117	13.0	1248	0.0753	0.8211	0.8707	0.8452	116	0.8333	0.8861	0.8589	158	0.9535	0.9919	0.9723	124	0.8667	0.9146	0.8900	0.9783
0.1055	14.0	1344	0.0695	0.8145	0.8707	0.8417	116	0.8415	0.8734	0.8571	158	0.9609	0.9919	0.9762	124	0.8702	0.9095	0.8894	0.9783
0.1008	15.0	1440	0.0685	0.8443	0.8879	0.8655	116	0.8263	0.8734	0.8492	158	0.9389	0.9919	0.9647	124	0.8667	0.9146	0.8900	0.9772
0.0978	16.0	1536	0.0678	0.8062	0.8966	0.8490	116	0.8225	0.8797	0.8502	158	0.9462	0.9919	0.9685	124	0.8551	0.9196	0.8862	0.9764
0.0929	17.0	1632	0.0605	0.824	0.8879	0.8548	116	0.85	0.8608	0.8553	158	0.9609	0.9919	0.9762	124	0.8765	0.9095	0.8927	0.9797
0.0854	18.0	1728	0.0591	0.8346	0.9138	0.8724	116	0.8742	0.8797	0.8770	158	0.9762	0.9919	0.9840	124	0.8932	0.9246	0.9086	0.9811
0.0834	19.0	1824	0.0554	0.8618	0.9138	0.8870	116	0.8868	0.8924	0.8896	158	0.9685	0.9919	0.9801	124	0.9046	0.9296	0.9170	0.9824
0.0815	20.0	1920	0.0561	0.848	0.9138	0.8797	116	0.8812	0.8924	0.8868	158	0.9762	0.9919	0.9840	124	0.9002	0.9296	0.9147	0.9805
0.0807	21.0	2016	0.0549	0.8492	0.9224	0.8843	116	0.8659	0.8987	0.8820	158	0.9762	0.9919	0.9840	124	0.8942	0.9347	0.9140	0.9808
0.078	22.0	2112	0.0527	0.8689	0.9138	0.8908	116	0.8889	0.9114	0.9000	158	0.9762	0.9919	0.9840	124	0.9098	0.9372	0.9233	0.9824
0.0738	23.0	2208	0.0506	0.8710	0.9310	0.9	116	0.9045	0.8987	0.9016	158	0.9762	0.9919	0.9840	124	0.9165	0.9372	0.9267	0.9835
0.0733	24.0	2304	0.0498	0.8699	0.9224	0.8954	116	0.8812	0.8924	0.8868	158	0.9762	0.9919	0.9840	124	0.9071	0.9322	0.9195	0.9830
0.0704	25.0	2400	0.0477	0.8843	0.9224	0.9030	116	0.9051	0.9051	0.9051	158	0.9762	0.9919	0.9840	124	0.9210	0.9372	0.9290	0.9841
0.0698	26.0	2496	0.0467	0.8824	0.9052	0.8936	116	0.9006	0.9177	0.9091	158	0.9762	0.9919	0.9840	124	0.9187	0.9372	0.9279	0.9844
0.0666	27.0	2592	0.0470	0.8926	0.9310	0.9114	116	0.8795	0.9241	0.9012	158	0.9762	0.9919	0.9840	124	0.9128	0.9472	0.9297	0.9835
0.0649	28.0	2688	0.0465	0.9016	0.9483	0.9244	116	0.8855	0.9304	0.9074	158	0.9762	0.9919	0.9840	124	0.9179	0.9548	0.9360	0.9852
0.0648	29.0	2784	0.0445	0.8908	0.9138	0.9021	116	0.8970	0.9367	0.9164	158	0.9762	0.9919	0.9840	124	0.9195	0.9472	0.9332	0.9846
0.0614	30.0	2880	0.0440	0.9153	0.9310	0.9231	116	0.9024	0.9367	0.9193	158	0.9762	0.9919	0.9840	124	0.9289	0.9523	0.9404	0.9860
0.0618	31.0	2976	0.0422	0.9	0.9310	0.9153	116	0.9068	0.9241	0.9154	158	0.9762	0.9919	0.9840	124	0.9263	0.9472	0.9366	0.9857
0.0613	32.0	3072	0.0432	0.9008	0.9397	0.9198	116	0.9286	0.9051	0.9167	158	0.984	0.9919	0.9880	124	0.9375	0.9422	0.9398	0.9865
0.0581	33.0	3168	0.0426	0.9091	0.9483	0.9283	116	0.9119	0.9177	0.9148	158	0.9685	0.9919	0.9801	124	0.9287	0.9497	0.9391	0.9863
0.0586	34.0	3264	0.0422	0.9160	0.9397	0.9277	116	0.9182	0.9241	0.9211	158	0.9762	0.9919	0.9840	124	0.9356	0.9497	0.9426	0.9868
0.0557	35.0	3360	0.0408	0.9231	0.9310	0.9270	116	0.8970	0.9367	0.9164	158	0.9762	0.9919	0.9840	124	0.9289	0.9523	0.9404	0.9865
0.0531	36.0	3456	0.0419	0.9091	0.9483	0.9283	116	0.9018	0.9304	0.9159	158	0.9685	0.9919	0.9801	124	0.9246	0.9548	0.9394	0.9863
0.0546	37.0	3552	0.0402	0.9167	0.9483	0.9322	116	0.9241	0.9241	0.9241	158	0.9685	0.9919	0.9801	124	0.9358	0.9523	0.9440	0.9868
0.0521	38.0	3648	0.0395	0.9068	0.9224	0.9145	116	0.9245	0.9304	0.9274	158	0.984	0.9919	0.9880	124	0.9378	0.9472	0.9425	0.9871
0.0535	39.0	3744	0.0391	0.9237	0.9397	0.9316	116	0.9136	0.9367	0.9250	158	0.9762	0.9919	0.9840	124	0.9360	0.9548	0.9453	0.9874
0.0504	40.0	3840	0.0393	0.9167	0.9483	0.9322	116	0.9299	0.9241	0.9270	158	0.984	0.9919	0.9880	124	0.9428	0.9523	0.9475	0.9876
0.0511	41.0	3936	0.0392	0.9083	0.9397	0.9237	116	0.8957	0.9241	0.9097	158	0.9762	0.9919	0.9840	124	0.9242	0.9497	0.9368	0.9868
0.0481	42.0	4032	0.0379	0.9244	0.9483	0.9362	116	0.9304	0.9304	0.9304	158	0.984	0.9919	0.9880	124	0.9453	0.9548	0.95	0.9879
0.0509	43.0	4128	0.0386	0.9237	0.9397	0.9316	116	0.9245	0.9304	0.9274	158	0.984	0.9919	0.9880	124	0.9428	0.9523	0.9475	0.9879
0.0498	44.0	4224	0.0382	0.9167	0.9483	0.9322	116	0.9125	0.9241	0.9182	158	0.984	0.9919	0.9880	124	0.9358	0.9523	0.9440	0.9879
0.0468	45.0	4320	0.0376	0.9083	0.9397	0.9237	116	0.9241	0.9241	0.9241	158	0.984	0.9919	0.9880	124	0.9380	0.9497	0.9438	0.9876
0.0449	46.0	4416	0.0372	0.9167	0.9483	0.9322	116	0.9187	0.9304	0.9245	158	0.984	0.9919	0.9880	124	0.9383	0.9548	0.9465	0.9882
0.0466	47.0	4512	0.0368	0.9160	0.9397	0.9277	116	0.9074	0.9304	0.9187	158	0.9762	0.9919	0.9840	124	0.9312	0.9523	0.9416	0.9874
0.0439	48.0	4608	0.0372	0.9167	0.9483	0.9322	116	0.9080	0.9367	0.9221	158	0.984	0.9919	0.9880	124	0.9338	0.9573	0.9454	0.9882
0.045	49.0	4704	0.0369	0.9167	0.9483	0.9322	116	0.9187	0.9304	0.9245	158	0.984	0.9919	0.9880	124	0.9383	0.9548	0.9465	0.9882
0.0439	50.0	4800	0.0367	0.9167	0.9483	0.9322	116	0.9187	0.9304	0.9245	158	0.9762	0.9919	0.9840	124	0.9360	0.9548	0.9453	0.9885
0.0453	51.0	4896	0.0372	0.9083	0.9397	0.9237	116	0.9182	0.9241	0.9211	158	0.984	0.9919	0.9880	124	0.9356	0.9497	0.9426	0.9879
0.0447	52.0	4992	0.0365	0.9153	0.9310	0.9231	116	0.8855	0.9304	0.9074	158	0.9762	0.9919	0.9840	124	0.9220	0.9497	0.9356	0.9868
0.0424	53.0	5088	0.0366	0.9167	0.9483	0.9322	116	0.9313	0.9430	0.9371	158	0.9762	0.9919	0.9840	124	0.9409	0.9598	0.9502	0.9887
0.042	54.0	5184	0.0360	0.9160	0.9397	0.9277	116	0.9198	0.9430	0.9312	158	0.9762	0.9919	0.9840	124	0.9361	0.9573	0.9466	0.9882
0.0407	55.0	5280	0.0355	0.9160	0.9397	0.9277	116	0.9136	0.9367	0.9250	158	0.9762	0.9919	0.9840	124	0.9337	0.9548	0.9441	0.9879
0.0414	56.0	5376	0.0353	0.9160	0.9397	0.9277	116	0.9198	0.9430	0.9312	158	0.9762	0.9919	0.9840	124	0.9361	0.9573	0.9466	0.9882
0.0417	57.0	5472	0.0356	0.9160	0.9397	0.9277	116	0.9255	0.9430	0.9342	158	0.9762	0.9919	0.9840	124	0.9384	0.9573	0.9478	0.9885
0.0395	58.0	5568	0.0359	0.9167	0.9483	0.9322	116	0.9490	0.9430	0.9460	158	0.9762	0.9919	0.9840	124	0.9479	0.9598	0.9538	0.9890
0.0403	59.0	5664	0.0362	0.9160	0.9397	0.9277	116	0.9198	0.9430	0.9312	158	0.9762	0.9919	0.9840	124	0.9361	0.9573	0.9466	0.9876
0.0413	60.0	5760	0.0354	0.9167	0.9483	0.9322	116	0.9371	0.9430	0.9401	158	0.9762	0.9919	0.9840	124	0.9432	0.9598	0.9514	0.9890
0.0391	61.0	5856	0.0363	0.9083	0.9397	0.9237	116	0.9304	0.9304	0.9304	158	0.9762	0.9919	0.9840	124	0.9381	0.9523	0.9451	0.9887
0.0381	62.0	5952	0.0360	0.9167	0.9483	0.9322	116	0.9371	0.9430	0.9401	158	0.9762	0.9919	0.9840	124	0.9432	0.9598	0.9514	0.9885
0.0388	63.0	6048	0.0359	0.9167	0.9483	0.9322	116	0.9313	0.9430	0.9371	158	0.9762	0.9919	0.9840	124	0.9409	0.9598	0.9502	0.9882
0.0377	64.0	6144	0.0364	0.8992	0.9224	0.9106	116	0.9308	0.9367	0.9338	158	0.984	0.9919	0.9880	124	0.9380	0.9497	0.9438	0.9887
0.0356	65.0	6240	0.0358	0.9167	0.9483	0.9322	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9455	0.9598	0.9526	0.9887
0.0377	66.0	6336	0.0358	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9762	0.9919	0.9840	124	0.9407	0.9573	0.9489	0.9882
0.0356	67.0	6432	0.0357	0.9076	0.9310	0.9191	116	0.9308	0.9367	0.9338	158	0.9762	0.9919	0.9840	124	0.9381	0.9523	0.9451	0.9885
0.0363	68.0	6528	0.0353	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.984	0.9919	0.9880	124	0.9454	0.9573	0.9513	0.9893
0.0354	69.0	6624	0.0352	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.984	0.9919	0.9880	124	0.9454	0.9573	0.9513	0.9893
0.0371	70.0	6720	0.0349	0.9160	0.9397	0.9277	116	0.9255	0.9430	0.9342	158	0.9685	0.9919	0.9801	124	0.9361	0.9573	0.9466	0.9882
0.035	71.0	6816	0.0347	0.9160	0.9397	0.9277	116	0.9255	0.9430	0.9342	158	0.984	0.9919	0.9880	124	0.9407	0.9573	0.9489	0.9887
0.0352	72.0	6912	0.0356	0.9167	0.9483	0.9322	116	0.9427	0.9367	0.9397	158	0.9762	0.9919	0.9840	124	0.9454	0.9573	0.9513	0.9896
0.0346	73.0	7008	0.0349	0.9160	0.9397	0.9277	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9454	0.9573	0.9513	0.9887
0.036	74.0	7104	0.0350	0.9076	0.9310	0.9191	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9429	0.9548	0.9488	0.9890
0.0355	75.0	7200	0.0346	0.9076	0.9310	0.9191	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9429	0.9548	0.9488	0.9893
0.0341	76.0	7296	0.0348	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.0336	77.0	7392	0.0350	0.9167	0.9483	0.9322	116	0.9487	0.9367	0.9427	158	0.984	0.9919	0.9880	124	0.9501	0.9573	0.9537	0.9896
0.0339	78.0	7488	0.0341	0.9160	0.9397	0.9277	116	0.9255	0.9430	0.9342	158	0.9685	0.9919	0.9801	124	0.9361	0.9573	0.9466	0.9882
0.034	79.0	7584	0.0350	0.9160	0.9397	0.9277	116	0.9141	0.9430	0.9283	158	0.9685	0.9919	0.9801	124	0.9315	0.9573	0.9442	0.9876
0.0345	80.0	7680	0.0346	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.0335	81.0	7776	0.0344	0.9160	0.9397	0.9277	116	0.9198	0.9430	0.9312	158	0.9685	0.9919	0.9801	124	0.9338	0.9573	0.9454	0.9879
0.0326	82.0	7872	0.0342	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.034	83.0	7968	0.0339	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.0329	84.0	8064	0.0347	0.9167	0.9483	0.9322	116	0.9430	0.9430	0.9430	158	0.9685	0.9919	0.9801	124	0.9432	0.9598	0.9514	0.9885
0.0344	85.0	8160	0.0342	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.0321	86.0	8256	0.0342	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9762	0.9919	0.9840	124	0.9431	0.9573	0.9501	0.9885
0.0323	87.0	8352	0.0346	0.9167	0.9483	0.9322	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9455	0.9598	0.9526	0.9887
0.0316	88.0	8448	0.0345	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0312	89.0	8544	0.0348	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0324	90.0	8640	0.0347	0.9160	0.9397	0.9277	116	0.9490	0.9430	0.9460	158	0.9762	0.9919	0.9840	124	0.9478	0.9573	0.9525	0.9893
0.0338	91.0	8736	0.0343	0.9076	0.9310	0.9191	116	0.9430	0.9430	0.9430	158	0.9685	0.9919	0.9801	124	0.9406	0.9548	0.9476	0.9890
0.0319	92.0	8832	0.0340	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0322	93.0	8928	0.0339	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9887
0.031	94.0	9024	0.0338	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.0337	95.0	9120	0.0339	0.9160	0.9397	0.9277	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9384	0.9573	0.9478	0.9885
0.0324	96.0	9216	0.0339	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0318	97.0	9312	0.0339	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0323	98.0	9408	0.0341	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0316	99.0	9504	0.0341	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882
0.0325	100.0	9600	0.0340	0.9160	0.9397	0.9277	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9882

Framework versions

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