nerui-seq_bn-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: 0.0410
• Location Precision: 0.9417
• Location Recall: 0.9741
• Location F1: 0.9576
• Location Number: 116
• Organization Precision: 0.9548
• Organization Recall: 0.9367
• Organization F1: 0.9457
• Organization Number: 158
• Person Precision: 0.9762
• Person Recall: 0.9919
• Person F1: 0.9840
• Person Number: 124
• Overall Precision: 0.9576
• Overall Recall: 0.9648
• Overall F1: 0.9612
• Overall Accuracy: 0.9896

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
0.8476	1.0	96	0.5342	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
0.4619	2.0	192	0.3106	0.4107	0.1983	0.2674	116	0.3641	0.4494	0.4023	158	0.3202	0.5242	0.3976	124	0.3502	0.3995	0.3732	0.8998
0.309	3.0	288	0.2281	0.4298	0.4224	0.4261	116	0.5021	0.7468	0.6005	158	0.5952	0.8065	0.6849	124	0.5164	0.6709	0.5836	0.9385
0.2191	4.0	384	0.1372	0.5969	0.6638	0.6286	116	0.6848	0.7975	0.7368	158	0.8369	0.9516	0.8906	124	0.7070	0.8065	0.7535	0.9624
0.1534	5.0	480	0.0976	0.752	0.8103	0.7801	116	0.7706	0.8291	0.7988	158	0.9104	0.9839	0.9457	124	0.8089	0.8719	0.8392	0.9728
0.1245	6.0	576	0.0794	0.8175	0.8879	0.8512	116	0.7917	0.8418	0.8160	158	0.9318	0.9919	0.9609	124	0.8427	0.9020	0.8714	0.9764
0.1074	7.0	672	0.0701	0.832	0.8966	0.8631	116	0.8405	0.8671	0.8536	158	0.9535	0.9919	0.9723	124	0.8729	0.9146	0.8933	0.9800
0.0956	8.0	768	0.0613	0.8413	0.9138	0.8760	116	0.8580	0.8797	0.8688	158	0.9609	0.9919	0.9762	124	0.8846	0.9246	0.9042	0.9819
0.0854	9.0	864	0.0615	0.864	0.9310	0.8963	116	0.8161	0.8987	0.8554	158	0.9535	0.9919	0.9723	124	0.8715	0.9372	0.9031	0.9802
0.0781	10.0	960	0.0559	0.8770	0.9224	0.8992	116	0.8494	0.8924	0.8704	158	0.9535	0.9919	0.9723	124	0.8897	0.9322	0.9104	0.9819
0.0773	11.0	1056	0.0502	0.872	0.9397	0.9046	116	0.8773	0.9051	0.8910	158	0.9609	0.9919	0.9762	124	0.9014	0.9422	0.9214	0.9838
0.0701	12.0	1152	0.0493	0.9008	0.9397	0.9198	116	0.8896	0.9177	0.9034	158	0.9531	0.9839	0.9683	124	0.9126	0.9447	0.9284	0.9846
0.0653	13.0	1248	0.0436	0.9316	0.9397	0.9356	116	0.9177	0.9177	0.9177	158	0.9685	0.9919	0.9801	124	0.9378	0.9472	0.9425	0.9863
0.0636	14.0	1344	0.0463	0.888	0.9569	0.9212	116	0.8968	0.8797	0.8882	158	0.9685	0.9919	0.9801	124	0.9165	0.9372	0.9267	0.9838
0.0611	15.0	1440	0.0423	0.9160	0.9397	0.9277	116	0.9125	0.9241	0.9182	158	0.9685	0.9919	0.9801	124	0.9310	0.9497	0.9403	0.9868
0.0613	16.0	1536	0.0437	0.9032	0.9655	0.9333	116	0.8639	0.9241	0.8930	158	0.9762	0.9919	0.9840	124	0.9093	0.9573	0.9327	0.9857
0.0625	17.0	1632	0.0420	0.9333	0.9655	0.9492	116	0.9241	0.9241	0.9241	158	0.9685	0.9919	0.9801	124	0.9407	0.9573	0.9489	0.9874
0.0532	18.0	1728	0.0368	0.9322	0.9483	0.9402	116	0.9074	0.9304	0.9187	158	0.984	0.9919	0.9880	124	0.9383	0.9548	0.9465	0.9879
0.0501	19.0	1824	0.0369	0.9652	0.9569	0.9610	116	0.9130	0.9304	0.9216	158	0.984	0.9919	0.9880	124	0.9501	0.9573	0.9537	0.9890
0.047	20.0	1920	0.0409	0.8943	0.9483	0.9205	116	0.8810	0.9367	0.9080	158	0.9685	0.9919	0.9801	124	0.9115	0.9573	0.9338	0.9855
0.0464	21.0	2016	0.0365	0.8943	0.9483	0.9205	116	0.9062	0.9177	0.9119	158	0.9762	0.9919	0.9840	124	0.9242	0.9497	0.9368	0.9865
0.045	22.0	2112	0.0363	0.9328	0.9569	0.9447	116	0.8862	0.9367	0.9108	158	0.984	0.9919	0.9880	124	0.9294	0.9598	0.9444	0.9876
0.0416	23.0	2208	0.0357	0.9256	0.9655	0.9451	116	0.9182	0.9241	0.9211	158	0.984	0.9919	0.9880	124	0.9407	0.9573	0.9489	0.9887
0.042	24.0	2304	0.0373	0.925	0.9569	0.9407	116	0.9231	0.9114	0.9172	158	0.984	0.9919	0.9880	124	0.9426	0.9497	0.9462	0.9876
0.0394	25.0	2400	0.0363	0.9328	0.9569	0.9447	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9433	0.9623	0.9527	0.9885
0.0362	26.0	2496	0.0338	0.9573	0.9655	0.9614	116	0.9259	0.9494	0.9375	158	0.9762	0.9919	0.9840	124	0.9506	0.9673	0.9589	0.9898
0.0379	27.0	2592	0.0337	0.9573	0.9655	0.9614	116	0.9085	0.9430	0.9255	158	0.9762	0.9919	0.9840	124	0.9435	0.9648	0.9540	0.9890
0.0328	28.0	2688	0.0362	0.9316	0.9397	0.9356	116	0.8869	0.9430	0.9141	158	0.9685	0.9919	0.9801	124	0.9248	0.9573	0.9407	0.9865
0.0347	29.0	2784	0.0354	0.9412	0.9655	0.9532	116	0.8982	0.9494	0.9231	158	0.9762	0.9919	0.9840	124	0.9345	0.9673	0.9506	0.9876
0.0314	30.0	2880	0.0360	0.9483	0.9483	0.9483	116	0.8922	0.9430	0.9169	158	0.9762	0.9919	0.9840	124	0.9340	0.9598	0.9467	0.9874
0.0312	31.0	2976	0.0323	0.9333	0.9655	0.9492	116	0.9193	0.9367	0.9279	158	0.9762	0.9919	0.9840	124	0.9410	0.9623	0.9516	0.9879
0.0295	32.0	3072	0.0314	0.9412	0.9655	0.9532	116	0.9554	0.9494	0.9524	158	0.984	0.9919	0.9880	124	0.9601	0.9673	0.9637	0.9907
0.0276	33.0	3168	0.0348	0.9492	0.9655	0.9573	116	0.9308	0.9367	0.9338	158	0.9762	0.9919	0.9840	124	0.9504	0.9623	0.9563	0.9893
0.0291	34.0	3264	0.0333	0.9339	0.9741	0.9536	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9506	0.9673	0.9589	0.9904
0.0271	35.0	3360	0.0335	0.9402	0.9483	0.9442	116	0.9371	0.9430	0.9401	158	0.9762	0.9919	0.9840	124	0.9502	0.9598	0.9550	0.9898
0.0256	36.0	3456	0.0360	0.9417	0.9741	0.9576	116	0.9313	0.9430	0.9371	158	0.9762	0.9919	0.9840	124	0.9483	0.9673	0.9577	0.9896
0.0251	37.0	3552	0.0347	0.9417	0.9741	0.9576	116	0.9551	0.9430	0.9490	158	0.9762	0.9919	0.9840	124	0.9577	0.9673	0.9625	0.9901
0.0253	38.0	3648	0.0353	0.9328	0.9569	0.9447	116	0.9367	0.9367	0.9367	158	0.9762	0.9919	0.9840	124	0.9479	0.9598	0.9538	0.9887
0.0248	39.0	3744	0.0338	0.9167	0.9483	0.9322	116	0.9313	0.9430	0.9371	158	0.9685	0.9919	0.9801	124	0.9386	0.9598	0.9491	0.9893
0.0222	40.0	3840	0.0334	0.9407	0.9569	0.9487	116	0.9437	0.9557	0.9497	158	0.9762	0.9919	0.9840	124	0.9530	0.9673	0.9601	0.9896
0.0226	41.0	3936	0.0345	0.9492	0.9655	0.9573	116	0.9255	0.9430	0.9342	158	0.9762	0.9919	0.9840	124	0.9481	0.9648	0.9564	0.9898
0.0208	42.0	4032	0.0345	0.9412	0.9655	0.9532	116	0.9551	0.9430	0.9490	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9898
0.0227	43.0	4128	0.0355	0.9483	0.9483	0.9483	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9573	0.9573	0.9573	0.9887
0.0222	44.0	4224	0.0370	0.9412	0.9655	0.9532	116	0.9367	0.9367	0.9367	158	0.9762	0.9919	0.9840	124	0.9504	0.9623	0.9563	0.9893
0.0197	45.0	4320	0.0362	0.9412	0.9655	0.9532	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9574	0.9598	0.9586	0.9896
0.0189	46.0	4416	0.0375	0.9333	0.9655	0.9492	116	0.9308	0.9367	0.9338	158	0.9762	0.9919	0.9840	124	0.9457	0.9623	0.9539	0.9890
0.02	47.0	4512	0.0363	0.9412	0.9655	0.9532	116	0.9255	0.9430	0.9342	158	0.9762	0.9919	0.9840	124	0.9458	0.9648	0.9552	0.9893
0.0178	48.0	4608	0.0369	0.9492	0.9655	0.9573	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9599	0.9623	0.9611	0.9893
0.02	49.0	4704	0.0357	0.9412	0.9655	0.9532	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9575	0.9623	0.9599	0.9896
0.0178	50.0	4800	0.0368	0.9492	0.9655	0.9573	116	0.9673	0.9367	0.9518	158	0.9762	0.9919	0.9840	124	0.9647	0.9623	0.9635	0.9893
0.0192	51.0	4896	0.0337	0.9412	0.9655	0.9532	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9529	0.9648	0.9588	0.9898
0.0173	52.0	4992	0.0352	0.9492	0.9655	0.9573	116	0.9615	0.9494	0.9554	158	0.9762	0.9919	0.9840	124	0.9625	0.9673	0.9649	0.9904
0.0169	53.0	5088	0.0353	0.9492	0.9655	0.9573	116	0.9434	0.9494	0.9464	158	0.9762	0.9919	0.9840	124	0.9553	0.9673	0.9613	0.9890
0.0153	54.0	5184	0.0351	0.9573	0.9655	0.9614	116	0.9618	0.9557	0.9587	158	0.9762	0.9919	0.9840	124	0.965	0.9698	0.9674	0.9898
0.0145	55.0	5280	0.0349	0.9492	0.9655	0.9573	116	0.9613	0.9430	0.9521	158	0.9762	0.9919	0.9840	124	0.9624	0.9648	0.9636	0.9898
0.0155	56.0	5376	0.0360	0.9417	0.9741	0.9576	116	0.9490	0.9430	0.9460	158	0.9762	0.9919	0.9840	124	0.9553	0.9673	0.9613	0.9901
0.016	57.0	5472	0.0376	0.9573	0.9655	0.9614	116	0.9613	0.9430	0.9521	158	0.9762	0.9919	0.9840	124	0.9648	0.9648	0.9648	0.9898
0.0143	58.0	5568	0.0389	0.9412	0.9655	0.9532	116	0.9671	0.9304	0.9484	158	0.9762	0.9919	0.9840	124	0.9622	0.9598	0.9610	0.9893
0.0156	59.0	5664	0.0370	0.9333	0.9655	0.9492	116	0.9427	0.9367	0.9397	158	0.9762	0.9919	0.9840	124	0.9504	0.9623	0.9563	0.9901
0.0152	60.0	5760	0.0367	0.9412	0.9655	0.9532	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9574	0.9598	0.9586	0.9896
0.0144	61.0	5856	0.0407	0.9333	0.9655	0.9492	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.955	0.9598	0.9574	0.9893
0.0127	62.0	5952	0.0389	0.9407	0.9569	0.9487	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9573	0.9573	0.9573	0.9890
0.0149	63.0	6048	0.0402	0.9328	0.9569	0.9447	116	0.9304	0.9304	0.9304	158	0.9762	0.9919	0.9840	124	0.9454	0.9573	0.9513	0.9879
0.0119	64.0	6144	0.0412	0.9316	0.9397	0.9356	116	0.9545	0.9304	0.9423	158	0.9685	0.9919	0.9801	124	0.9523	0.9523	0.9523	0.9887
0.0117	65.0	6240	0.0380	0.9407	0.9569	0.9487	116	0.9542	0.9241	0.9389	158	0.9762	0.9919	0.9840	124	0.9572	0.9548	0.9560	0.9887
0.013	66.0	6336	0.0384	0.9402	0.9483	0.9442	116	0.9542	0.9241	0.9389	158	0.9762	0.9919	0.9840	124	0.9571	0.9523	0.9547	0.9885
0.012	67.0	6432	0.0413	0.9492	0.9655	0.9573	116	0.9735	0.9304	0.9515	158	0.9762	0.9919	0.9840	124	0.9671	0.9598	0.9634	0.9893
0.0112	68.0	6528	0.0399	0.9492	0.9655	0.9573	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9599	0.9623	0.9611	0.9896
0.0129	69.0	6624	0.0367	0.9652	0.9569	0.9610	116	0.9490	0.9430	0.9460	158	0.9762	0.9919	0.9840	124	0.9623	0.9623	0.9623	0.9898
0.0115	70.0	6720	0.0381	0.9333	0.9655	0.9492	116	0.9427	0.9367	0.9397	158	0.9762	0.9919	0.9840	124	0.9504	0.9623	0.9563	0.9890
0.0119	71.0	6816	0.0381	0.9412	0.9655	0.9532	116	0.9608	0.9304	0.9453	158	0.9762	0.9919	0.9840	124	0.9598	0.9598	0.9598	0.9890
0.0127	72.0	6912	0.0418	0.9492	0.9655	0.9573	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9598	0.9598	0.9598	0.9890
0.011	73.0	7008	0.0408	0.9412	0.9655	0.9532	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9551	0.9623	0.9587	0.9890
0.0121	74.0	7104	0.0426	0.9333	0.9655	0.9492	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.955	0.9598	0.9574	0.9890
0.0122	75.0	7200	0.0391	0.9412	0.9655	0.9532	116	0.9484	0.9304	0.9393	158	0.9762	0.9919	0.9840	124	0.955	0.9598	0.9574	0.9893
0.0108	76.0	7296	0.0401	0.9412	0.9655	0.9532	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9551	0.9623	0.9587	0.9890
0.0103	77.0	7392	0.0402	0.9412	0.9655	0.9532	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9574	0.9598	0.9586	0.9887
0.0105	78.0	7488	0.0404	0.9417	0.9741	0.9576	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9896
0.0106	79.0	7584	0.0419	0.9417	0.9741	0.9576	116	0.9671	0.9304	0.9484	158	0.9762	0.9919	0.9840	124	0.9623	0.9623	0.9623	0.9896
0.0111	80.0	7680	0.0401	0.9492	0.9655	0.9573	116	0.9490	0.9430	0.9460	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9893
0.0109	81.0	7776	0.0395	0.9492	0.9655	0.9573	116	0.9313	0.9430	0.9371	158	0.9762	0.9919	0.9840	124	0.9505	0.9648	0.9576	0.9896
0.0093	82.0	7872	0.0401	0.9333	0.9655	0.9492	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9527	0.9623	0.9575	0.9898
0.0097	83.0	7968	0.0397	0.9412	0.9655	0.9532	116	0.9430	0.9430	0.9430	158	0.9762	0.9919	0.9840	124	0.9529	0.9648	0.9588	0.9901
0.0099	84.0	8064	0.0411	0.9417	0.9741	0.9576	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9552	0.9648	0.96	0.9898
0.0109	85.0	8160	0.0399	0.9492	0.9655	0.9573	116	0.9371	0.9430	0.9401	158	0.9762	0.9919	0.9840	124	0.9529	0.9648	0.9588	0.9898
0.0086	86.0	8256	0.0415	0.9333	0.9655	0.9492	116	0.9484	0.9304	0.9393	158	0.9762	0.9919	0.9840	124	0.9526	0.9598	0.9562	0.9890
0.0099	87.0	8352	0.0413	0.9333	0.9655	0.9492	116	0.9308	0.9367	0.9338	158	0.9762	0.9919	0.9840	124	0.9457	0.9623	0.9539	0.9896
0.0096	88.0	8448	0.0412	0.9487	0.9569	0.9528	116	0.925	0.9367	0.9308	158	0.9762	0.9919	0.9840	124	0.9479	0.9598	0.9538	0.9893
0.0092	89.0	8544	0.0424	0.9417	0.9741	0.9576	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9896
0.0095	90.0	8640	0.0422	0.9412	0.9655	0.9532	116	0.9484	0.9304	0.9393	158	0.9762	0.9919	0.9840	124	0.955	0.9598	0.9574	0.9893
0.0097	91.0	8736	0.0420	0.9333	0.9655	0.9492	116	0.9608	0.9304	0.9453	158	0.9762	0.9919	0.9840	124	0.9574	0.9598	0.9586	0.9893
0.0089	92.0	8832	0.0410	0.9407	0.9569	0.9487	116	0.9423	0.9304	0.9363	158	0.9762	0.9919	0.9840	124	0.9525	0.9573	0.9549	0.9887
0.009	93.0	8928	0.0400	0.9333	0.9655	0.9492	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9527	0.9623	0.9575	0.9893
0.0087	94.0	9024	0.0399	0.9407	0.9569	0.9487	116	0.9363	0.9304	0.9333	158	0.9762	0.9919	0.9840	124	0.9501	0.9573	0.9537	0.9890
0.0104	95.0	9120	0.0406	0.9333	0.9655	0.9492	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9527	0.9623	0.9575	0.9893
0.0096	96.0	9216	0.0407	0.9417	0.9741	0.9576	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9896
0.009	97.0	9312	0.0406	0.9412	0.9655	0.9532	116	0.9487	0.9367	0.9427	158	0.9762	0.9919	0.9840	124	0.9551	0.9623	0.9587	0.9890
0.0077	98.0	9408	0.0411	0.9417	0.9741	0.9576	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9896
0.0089	99.0	9504	0.0410	0.9417	0.9741	0.9576	116	0.9545	0.9304	0.9423	158	0.9762	0.9919	0.9840	124	0.9575	0.9623	0.9599	0.9893
0.0088	100.0	9600	0.0410	0.9417	0.9741	0.9576	116	0.9548	0.9367	0.9457	158	0.9762	0.9919	0.9840	124	0.9576	0.9648	0.9612	0.9896

Framework versions

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