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apwic/
nerui-pt-pl30-1

Name: nerui-pt-pl30-1
Availability: InStock

tensorboard

generated_from_trainer

indolem/indobert-base-uncased

finetune

mit

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nerui-pt-pl30-1

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: 0.0474
Location Precision: 0.9407
Location Recall: 0.9569
Location F1: 0.9487
Location Number: 116
Organization Precision: 0.9675
Organization Recall: 0.9430
Organization F1: 0.9551
Organization Number: 158
Person Precision: 0.9685
Person Recall: 0.9919
Person F1: 0.9801
Person Number: 124
Overall Precision: 0.9599
Overall Recall: 0.9623
Overall F1: 0.9611
Overall Accuracy: 0.9912

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
0.8685	1.0	96	0.4002	0.0	0.0	0.0	116	0.2589	0.1835	0.2148	158	0.3131	0.25	0.2780	124	0.2817	0.1508	0.1964	0.8600
0.3663	2.0	192	0.2149	0.3	0.3879	0.3383	116	0.5629	0.5380	0.5502	158	0.6084	0.8145	0.6966	124	0.4946	0.5804	0.5341	0.9286
0.2004	3.0	288	0.1089	0.8108	0.7759	0.7930	116	0.7033	0.8101	0.7529	158	0.8971	0.9839	0.9385	124	0.7925	0.8543	0.8222	0.9673
0.1345	4.0	384	0.0808	0.7698	0.9224	0.8392	116	0.8121	0.8481	0.8297	158	0.9462	0.9919	0.9685	124	0.8387	0.9146	0.8750	0.9731
0.1084	5.0	480	0.0553	0.8938	0.8707	0.8821	116	0.8938	0.9051	0.8994	158	0.9685	0.9919	0.9801	124	0.9175	0.9221	0.9198	0.9835
0.0959	6.0	576	0.0483	0.8385	0.9397	0.8862	116	0.8834	0.9114	0.8972	158	0.9762	0.9919	0.9840	124	0.8974	0.9447	0.9204	0.9855
0.0827	7.0	672	0.0428	0.9455	0.8966	0.9204	116	0.8523	0.9494	0.8982	158	0.9839	0.9839	0.9839	124	0.9171	0.9447	0.9307	0.9871
0.08	8.0	768	0.0381	0.9145	0.9224	0.9185	116	0.9136	0.9367	0.9250	158	0.976	0.9839	0.9799	124	0.9332	0.9472	0.9401	0.9896
0.0729	9.0	864	0.0486	0.872	0.9397	0.9046	116	0.9141	0.9430	0.9283	158	0.9762	0.9919	0.9840	124	0.9203	0.9573	0.9384	0.9844
0.0635	10.0	960	0.0435	0.8425	0.9224	0.8807	116	0.9136	0.9367	0.9250	158	0.9685	0.9919	0.9801	124	0.9087	0.9497	0.9287	0.9857
0.0614	11.0	1056	0.0421	0.8594	0.9483	0.9016	116	0.94	0.8924	0.9156	158	0.9762	0.9919	0.9840	124	0.9257	0.9397	0.9327	0.9865
0.0561	12.0	1152	0.0318	0.8852	0.9310	0.9076	116	0.9416	0.9177	0.9295	158	0.9762	0.9919	0.9840	124	0.9353	0.9447	0.94	0.9882
0.0546	13.0	1248	0.0305	0.9322	0.9483	0.9402	116	0.9371	0.9430	0.9401	158	0.9685	0.9919	0.9801	124	0.9455	0.9598	0.9526	0.9915
0.0475	14.0	1344	0.0348	0.9231	0.9310	0.9270	116	0.9484	0.9304	0.9393	158	0.976	0.9839	0.9799	124	0.9496	0.9472	0.9484	0.9896
0.0464	15.0	1440	0.0338	0.925	0.9569	0.9407	116	0.9423	0.9304	0.9363	158	0.9762	0.9919	0.9840	124	0.9478	0.9573	0.9525	0.9904
0.0428	16.0	1536	0.0317	0.9167	0.9483	0.9322	116	0.9430	0.9430	0.9430	158	0.976	0.9839	0.9799	124	0.9454	0.9573	0.9513	0.9907
0.0417	17.0	1632	0.0322	0.925	0.9569	0.9407	116	0.9419	0.9241	0.9329	158	0.9762	0.9919	0.9840	124	0.9476	0.9548	0.9512	0.9912
0.0388	18.0	1728	0.0332	0.9322	0.9483	0.9402	116	0.9551	0.9430	0.9490	158	0.9839	0.9839	0.9839	124	0.9573	0.9573	0.9573	0.9909
0.0366	19.0	1824	0.0317	0.9068	0.9224	0.9145	116	0.925	0.9367	0.9308	158	0.9762	0.9919	0.9840	124	0.9356	0.9497	0.9426	0.9909
0.0373	20.0	1920	0.0352	0.9083	0.9397	0.9237	116	0.9423	0.9304	0.9363	158	0.9762	0.9919	0.9840	124	0.9428	0.9523	0.9475	0.9893
0.0363	21.0	2016	0.0348	0.9106	0.9655	0.9372	116	0.9608	0.9304	0.9453	158	0.9762	0.9919	0.9840	124	0.9502	0.9598	0.9550	0.9901
0.0333	22.0	2112	0.0326	0.9402	0.9483	0.9442	116	0.9675	0.9430	0.9551	158	0.9762	0.9919	0.9840	124	0.9622	0.9598	0.9610	0.9920
0.0334	23.0	2208	0.0332	0.9244	0.9483	0.9362	116	0.9603	0.9177	0.9385	158	0.9839	0.9839	0.9839	124	0.9569	0.9472	0.9520	0.9907
0.0311	24.0	2304	0.0336	0.9316	0.9397	0.9356	116	0.9542	0.9241	0.9389	158	0.9762	0.9919	0.9840	124	0.9545	0.9497	0.9521	0.9912
0.0291	25.0	2400	0.0459	0.8682	0.9655	0.9143	116	0.9608	0.9304	0.9453	158	0.9685	0.9919	0.9801	124	0.9340	0.9598	0.9467	0.9887
0.0309	26.0	2496	0.0323	0.9407	0.9569	0.9487	116	0.9610	0.9367	0.9487	158	0.9839	0.9839	0.9839	124	0.9621	0.9573	0.9597	0.9923
0.03	27.0	2592	0.0337	0.9316	0.9397	0.9356	116	0.9539	0.9177	0.9355	158	0.9762	0.9919	0.9840	124	0.9544	0.9472	0.9508	0.9898
0.0251	28.0	2688	0.0360	0.9083	0.9397	0.9237	116	0.9367	0.9367	0.9367	158	0.976	0.9839	0.9799	124	0.9404	0.9523	0.9463	0.9898
0.0228	29.0	2784	0.0436	0.9083	0.9397	0.9237	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9431	0.9573	0.9501	0.9890
0.0248	30.0	2880	0.0401	0.9138	0.9138	0.9138	116	0.9313	0.9430	0.9371	158	0.9762	0.9919	0.9840	124	0.9403	0.9497	0.9450	0.9890
0.0238	31.0	2976	0.0381	0.9412	0.9655	0.9532	116	0.9669	0.9241	0.9450	158	0.976	0.9839	0.9799	124	0.9620	0.9548	0.9584	0.9909
0.0213	32.0	3072	0.0407	0.9167	0.9483	0.9322	116	0.9419	0.9241	0.9329	158	0.976	0.9839	0.9799	124	0.945	0.9497	0.9474	0.9901
0.0222	33.0	3168	0.0342	0.9402	0.9483	0.9442	116	0.9539	0.9177	0.9355	158	0.9762	0.9919	0.9840	124	0.9570	0.9497	0.9533	0.9915
0.022	34.0	3264	0.0417	0.9083	0.9397	0.9237	116	0.9430	0.9430	0.9430	158	0.976	0.9839	0.9799	124	0.9429	0.9548	0.9488	0.9898
0.0217	35.0	3360	0.0404	0.9153	0.9310	0.9231	116	0.9490	0.9430	0.9460	158	0.9683	0.9839	0.976	124	0.9451	0.9523	0.9487	0.9909
0.0188	36.0	3456	0.0390	0.9474	0.9310	0.9391	116	0.9363	0.9304	0.9333	158	0.9609	0.9919	0.9762	124	0.9474	0.9497	0.9486	0.9909
0.0212	37.0	3552	0.0352	0.9643	0.9310	0.9474	116	0.9497	0.9557	0.9527	158	0.976	0.9839	0.9799	124	0.9621	0.9573	0.9597	0.9923
0.0183	38.0	3648	0.0390	0.9478	0.9397	0.9437	116	0.9434	0.9494	0.9464	158	0.976	0.9839	0.9799	124	0.9549	0.9573	0.9561	0.9915
0.0184	39.0	3744	0.0332	0.9483	0.9483	0.9483	116	0.9613	0.9430	0.9521	158	0.976	0.9839	0.9799	124	0.9621	0.9573	0.9597	0.9926
0.0176	40.0	3840	0.0409	0.9167	0.9483	0.9322	116	0.9608	0.9304	0.9453	158	0.9606	0.9839	0.9721	124	0.9475	0.9523	0.9499	0.9901
0.0182	41.0	3936	0.0388	0.9322	0.9483	0.9402	116	0.9554	0.9494	0.9524	158	0.9685	0.9919	0.9801	124	0.9527	0.9623	0.9575	0.9923
0.0175	42.0	4032	0.0399	0.9098	0.9569	0.9328	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.9480	0.9623	0.9551	0.9912
0.0169	43.0	4128	0.0381	0.9478	0.9397	0.9437	116	0.9245	0.9304	0.9274	158	0.9839	0.9839	0.9839	124	0.9497	0.9497	0.9497	0.9907
0.0166	44.0	4224	0.0399	0.9174	0.9569	0.9367	116	0.9613	0.9430	0.9521	158	0.9531	0.9839	0.9683	124	0.9455	0.9598	0.9526	0.9907
0.015	45.0	4320	0.0362	0.9333	0.9655	0.9492	116	0.9608	0.9304	0.9453	158	0.976	0.9839	0.9799	124	0.9573	0.9573	0.9573	0.9923
0.0163	46.0	4416	0.0411	0.9008	0.9397	0.9198	116	0.9548	0.9367	0.9457	158	0.9685	0.9919	0.9801	124	0.9429	0.9548	0.9488	0.9901
0.0163	47.0	4512	0.0393	0.9167	0.9483	0.9322	116	0.9608	0.9304	0.9453	158	0.9762	0.9919	0.9840	124	0.9524	0.9548	0.9536	0.9915
0.0136	48.0	4608	0.0423	0.9316	0.9397	0.9356	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9548	0.9548	0.9548	0.9915
0.0147	49.0	4704	0.0378	0.9397	0.9397	0.9397	116	0.9551	0.9430	0.9490	158	0.9839	0.9839	0.9839	124	0.9596	0.9548	0.9572	0.9920
0.0126	50.0	4800	0.0433	0.9316	0.9397	0.9356	116	0.9551	0.9430	0.9490	158	0.9683	0.9839	0.976	124	0.9524	0.9548	0.9536	0.9909
0.0146	51.0	4896	0.0448	0.9244	0.9483	0.9362	116	0.9608	0.9304	0.9453	158	0.9685	0.9919	0.9801	124	0.9524	0.9548	0.9536	0.9904
0.0146	52.0	4992	0.0469	0.9174	0.9569	0.9367	116	0.9669	0.9241	0.9450	158	0.9609	0.9919	0.9762	124	0.95	0.9548	0.9524	0.9904
0.0119	53.0	5088	0.0466	0.9160	0.9397	0.9277	116	0.9487	0.9367	0.9427	158	0.9609	0.9919	0.9762	124	0.9429	0.9548	0.9488	0.9898
0.0128	54.0	5184	0.0531	0.9167	0.9483	0.9322	116	0.9548	0.9367	0.9457	158	0.9609	0.9919	0.9762	124	0.9454	0.9573	0.9513	0.9893
0.013	55.0	5280	0.0437	0.9402	0.9483	0.9442	116	0.9481	0.9241	0.9359	158	0.9609	0.9919	0.9762	124	0.9499	0.9523	0.9511	0.9909
0.0125	56.0	5376	0.0464	0.9237	0.9397	0.9316	116	0.9542	0.9241	0.9389	158	0.9609	0.9919	0.9762	124	0.9474	0.9497	0.9486	0.9896
0.012	57.0	5472	0.0429	0.9397	0.9397	0.9397	116	0.9363	0.9304	0.9333	158	0.9685	0.9919	0.9801	124	0.9475	0.9523	0.9499	0.9904
0.012	58.0	5568	0.0482	0.9237	0.9397	0.9316	116	0.9484	0.9304	0.9393	158	0.9685	0.9919	0.9801	124	0.9475	0.9523	0.9499	0.9893
0.0123	59.0	5664	0.0561	0.9167	0.9483	0.9322	116	0.9416	0.9177	0.9295	158	0.9609	0.9919	0.9762	124	0.9403	0.9497	0.9450	0.9887
0.0117	60.0	5760	0.0506	0.9322	0.9483	0.9402	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9548	0.9548	0.9548	0.9898
0.0115	61.0	5856	0.0482	0.9322	0.9483	0.9402	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9548	0.9548	0.9548	0.9898
0.0094	62.0	5952	0.0504	0.9322	0.9483	0.9402	116	0.9484	0.9304	0.9393	158	0.984	0.9919	0.9880	124	0.9548	0.9548	0.9548	0.9901
0.0101	63.0	6048	0.0478	0.9322	0.9483	0.9402	116	0.9484	0.9304	0.9393	158	0.984	0.9919	0.9880	124	0.9548	0.9548	0.9548	0.9904
0.0096	64.0	6144	0.0485	0.9322	0.9483	0.9402	116	0.9608	0.9304	0.9453	158	0.984	0.9919	0.9880	124	0.9596	0.9548	0.9572	0.9915
0.0095	65.0	6240	0.0578	0.9244	0.9483	0.9362	116	0.9545	0.9304	0.9423	158	0.9609	0.9919	0.9762	124	0.9476	0.9548	0.9512	0.9896
0.0113	66.0	6336	0.0549	0.925	0.9569	0.9407	116	0.9605	0.9241	0.9419	158	0.9685	0.9919	0.9801	124	0.9524	0.9548	0.9536	0.9904
0.0088	67.0	6432	0.0499	0.9322	0.9483	0.9402	116	0.9484	0.9304	0.9393	158	0.9609	0.9919	0.9762	124	0.9476	0.9548	0.9512	0.9901
0.0094	68.0	6528	0.0439	0.9402	0.9483	0.9442	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9573	0.9573	0.9573	0.9912
0.008	69.0	6624	0.0484	0.9402	0.9483	0.9442	116	0.9613	0.9430	0.9521	158	0.9762	0.9919	0.9840	124	0.9598	0.9598	0.9598	0.9907
0.0092	70.0	6720	0.0447	0.9322	0.9483	0.9402	116	0.9484	0.9304	0.9393	158	0.9685	0.9919	0.9801	124	0.95	0.9548	0.9524	0.9907
0.008	71.0	6816	0.0524	0.9244	0.9483	0.9362	116	0.9481	0.9241	0.9359	158	0.9762	0.9919	0.9840	124	0.9499	0.9523	0.9511	0.9898
0.0084	72.0	6912	0.0443	0.9322	0.9483	0.9402	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9549	0.9573	0.9561	0.9909
0.0085	73.0	7008	0.0468	0.9402	0.9483	0.9442	116	0.9551	0.9430	0.9490	158	0.9685	0.9919	0.9801	124	0.955	0.9598	0.9574	0.9909
0.0081	74.0	7104	0.0473	0.9322	0.9483	0.9402	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9548	0.9548	0.9548	0.9912
0.0087	75.0	7200	0.0448	0.9328	0.9569	0.9447	116	0.9542	0.9241	0.9389	158	0.9685	0.9919	0.9801	124	0.9524	0.9548	0.9536	0.9912
0.0076	76.0	7296	0.0498	0.9244	0.9483	0.9362	116	0.9487	0.9367	0.9427	158	0.9685	0.9919	0.9801	124	0.9478	0.9573	0.9525	0.9904
0.0074	77.0	7392	0.0477	0.9322	0.9483	0.9402	116	0.9484	0.9304	0.9393	158	0.9685	0.9919	0.9801	124	0.95	0.9548	0.9524	0.9907
0.008	78.0	7488	0.0429	0.9407	0.9569	0.9487	116	0.9613	0.9430	0.9521	158	0.984	0.9919	0.9880	124	0.9623	0.9623	0.9623	0.9923
0.0072	79.0	7584	0.0491	0.9244	0.9483	0.9362	116	0.9545	0.9304	0.9423	158	0.9609	0.9919	0.9762	124	0.9476	0.9548	0.9512	0.9896
0.0066	80.0	7680	0.0501	0.925	0.9569	0.9407	116	0.9673	0.9367	0.9518	158	0.9685	0.9919	0.9801	124	0.955	0.9598	0.9574	0.9912
0.0068	81.0	7776	0.0472	0.9322	0.9483	0.9402	116	0.9548	0.9367	0.9457	158	0.9685	0.9919	0.9801	124	0.9525	0.9573	0.9549	0.9907
0.0066	82.0	7872	0.0534	0.9322	0.9483	0.9402	116	0.9613	0.9430	0.9521	158	0.9609	0.9919	0.9762	124	0.9526	0.9598	0.9562	0.9901
0.0069	83.0	7968	0.0481	0.9322	0.9483	0.9402	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9549	0.9573	0.9561	0.9909
0.0065	84.0	8064	0.0521	0.9322	0.9483	0.9402	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.955	0.9598	0.9574	0.9904
0.0063	85.0	8160	0.0548	0.9322	0.9483	0.9402	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.955	0.9598	0.9574	0.9904
0.0064	86.0	8256	0.0527	0.9322	0.9483	0.9402	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.955	0.9598	0.9574	0.9904
0.007	87.0	8352	0.0479	0.9402	0.9483	0.9442	116	0.9551	0.9430	0.9490	158	0.9685	0.9919	0.9801	124	0.955	0.9598	0.9574	0.9909
0.0062	88.0	8448	0.0478	0.9402	0.9483	0.9442	116	0.9675	0.9430	0.9551	158	0.9762	0.9919	0.9840	124	0.9622	0.9598	0.9610	0.9918
0.0057	89.0	8544	0.0476	0.9402	0.9483	0.9442	116	0.9613	0.9430	0.9521	158	0.9762	0.9919	0.9840	124	0.9598	0.9598	0.9598	0.9909
0.0058	90.0	8640	0.0475	0.9402	0.9483	0.9442	116	0.9610	0.9367	0.9487	158	0.9762	0.9919	0.9840	124	0.9597	0.9573	0.9585	0.9912
0.0066	91.0	8736	0.0508	0.9402	0.9483	0.9442	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.9574	0.9598	0.9586	0.9907
0.0061	92.0	8832	0.0507	0.9328	0.9569	0.9447	116	0.9675	0.9430	0.9551	158	0.9685	0.9919	0.9801	124	0.9575	0.9623	0.9599	0.9907
0.0065	93.0	8928	0.0476	0.9407	0.9569	0.9487	116	0.9739	0.9430	0.9582	158	0.9685	0.9919	0.9801	124	0.9623	0.9623	0.9623	0.9920
0.0065	94.0	9024	0.0497	0.9402	0.9483	0.9442	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.9574	0.9598	0.9586	0.9907
0.007	95.0	9120	0.0472	0.9402	0.9483	0.9442	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.9574	0.9598	0.9586	0.9912
0.0076	96.0	9216	0.0495	0.9407	0.9569	0.9487	116	0.9675	0.9430	0.9551	158	0.9685	0.9919	0.9801	124	0.9599	0.9623	0.9611	0.9909
0.0057	97.0	9312	0.0483	0.9407	0.9569	0.9487	116	0.9675	0.9430	0.9551	158	0.9685	0.9919	0.9801	124	0.9599	0.9623	0.9611	0.9912
0.0058	98.0	9408	0.0471	0.9402	0.9483	0.9442	116	0.9613	0.9430	0.9521	158	0.9685	0.9919	0.9801	124	0.9574	0.9598	0.9586	0.9909
0.0063	99.0	9504	0.0477	0.9407	0.9569	0.9487	116	0.9675	0.9430	0.9551	158	0.9685	0.9919	0.9801	124	0.9599	0.9623	0.9611	0.9912
0.0055	100.0	9600	0.0474	0.9407	0.9569	0.9487	116	0.9675	0.9430	0.9551	158	0.9685	0.9919	0.9801	124	0.9599	0.9623	0.9611	0.9912

Framework versions

Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.15.2

apwic/nerui-pt-pl30-1

nerui-pt-pl30-1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

apwic/
nerui-pt-pl30-1