nerui-pt-pl50-0

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: 0.0690
• Location Precision: 0.9
• Location Recall: 0.9574
• Location F1: 0.9278
• Location Number: 94
• Organization Precision: 0.9379
• Organization Recall: 0.9042
• Organization F1: 0.9207
• Organization Number: 167
• Person Precision: 0.9706
• Person Recall: 0.9635
• Person F1: 0.9670
• Person Number: 137
• Overall Precision: 0.9395
• Overall Recall: 0.9372
• Overall F1: 0.9384
• Overall Accuracy: 0.9881

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
0.8736	1.0	96	0.4345	0.0	0.0	0.0	94	0.2048	0.1018	0.1360	167	0.3019	0.1168	0.1684	137	0.2409	0.0829	0.1234	0.8453
0.3697	2.0	192	0.2212	0.3288	0.5106	0.4	94	0.5408	0.6347	0.5840	167	0.8207	0.8686	0.8440	137	0.5606	0.6859	0.6169	0.9312
0.203	3.0	288	0.1151	0.7723	0.8298	0.8000	94	0.7316	0.8323	0.7787	167	0.9184	0.9854	0.9507	137	0.8037	0.8844	0.8421	0.9660
0.1351	4.0	384	0.0815	0.7265	0.9043	0.8057	94	0.8187	0.7844	0.8012	167	0.9643	0.9854	0.9747	137	0.8417	0.8819	0.8613	0.9718
0.1121	5.0	480	0.0613	0.8866	0.9149	0.9005	94	0.8580	0.8683	0.8631	167	0.9926	0.9854	0.9890	137	0.9104	0.9196	0.9150	0.9807
0.0964	6.0	576	0.0584	0.8198	0.9681	0.8878	94	0.8788	0.8683	0.8735	167	0.9783	0.9854	0.9818	137	0.8961	0.9322	0.9138	0.9820
0.0832	7.0	672	0.0550	0.8558	0.9468	0.8990	94	0.8634	0.8323	0.8476	167	0.95	0.9708	0.9603	137	0.8914	0.9070	0.8991	0.9815
0.078	8.0	768	0.0495	0.8165	0.9468	0.8768	94	0.8742	0.8323	0.8528	167	0.9708	0.9708	0.9708	137	0.8914	0.9070	0.8991	0.9823
0.0701	9.0	864	0.0479	0.8108	0.9574	0.8780	94	0.8954	0.8204	0.8563	167	0.9710	0.9781	0.9745	137	0.8980	0.9070	0.9025	0.9831
0.0639	10.0	960	0.0465	0.89	0.9468	0.9175	94	0.8793	0.9162	0.8974	167	0.9638	0.9708	0.9673	137	0.9102	0.9422	0.9259	0.9854
0.0619	11.0	1056	0.0412	0.8911	0.9574	0.9231	94	0.9329	0.9162	0.9245	167	0.9854	0.9854	0.9854	137	0.9403	0.9497	0.9450	0.9873
0.056	12.0	1152	0.0478	0.8738	0.9574	0.9137	94	0.9167	0.8563	0.8854	167	1.0	0.9854	0.9926	137	0.9340	0.9246	0.9293	0.9862
0.0502	13.0	1248	0.0438	0.8725	0.9468	0.9082	94	0.9182	0.8743	0.8957	167	0.9779	0.9708	0.9744	137	0.9270	0.9246	0.9258	0.9862
0.0495	14.0	1344	0.0441	0.8505	0.9681	0.9055	94	0.9080	0.8862	0.8970	167	0.9853	0.9781	0.9817	137	0.9187	0.9372	0.9279	0.9854
0.0465	15.0	1440	0.0424	0.9072	0.9362	0.9215	94	0.9042	0.9042	0.9042	167	0.9779	0.9708	0.9744	137	0.93	0.9347	0.9323	0.9870
0.045	16.0	1536	0.0447	0.8969	0.9255	0.9110	94	0.8966	0.9341	0.9150	167	0.9779	0.9708	0.9744	137	0.9238	0.9447	0.9342	0.9865
0.0427	17.0	1632	0.0470	0.8889	0.9362	0.9119	94	0.9146	0.8982	0.9063	167	0.9779	0.9708	0.9744	137	0.9298	0.9322	0.9310	0.9865
0.04	18.0	1728	0.0523	0.8725	0.9468	0.9082	94	0.875	0.8383	0.8563	167	0.9853	0.9781	0.9817	137	0.9121	0.9121	0.9121	0.9826
0.0402	19.0	1824	0.0501	0.9062	0.9255	0.9158	94	0.9085	0.8922	0.9003	167	0.9779	0.9708	0.9744	137	0.9318	0.9271	0.9295	0.9865
0.0382	20.0	1920	0.0509	0.9082	0.9468	0.9271	94	0.9157	0.9102	0.9129	167	0.9708	0.9708	0.9708	137	0.9327	0.9397	0.9362	0.9865
0.0356	21.0	2016	0.0450	0.9082	0.9468	0.9271	94	0.9162	0.9162	0.9162	167	0.9853	0.9781	0.9817	137	0.9377	0.9447	0.9412	0.9876
0.0352	22.0	2112	0.0510	0.9091	0.9574	0.9326	94	0.9212	0.9102	0.9157	167	0.9926	0.9781	0.9853	137	0.9424	0.9447	0.9435	0.9867
0.0316	23.0	2208	0.0481	0.89	0.9468	0.9175	94	0.9264	0.9042	0.9152	167	0.9779	0.9708	0.9744	137	0.9348	0.9372	0.9360	0.9870
0.03	24.0	2304	0.0503	0.8544	0.9362	0.8934	94	0.9321	0.9042	0.9179	167	0.9781	0.9781	0.9781	137	0.9279	0.9372	0.9325	0.9856
0.0304	25.0	2400	0.0464	0.88	0.9362	0.9072	94	0.9102	0.9102	0.9102	167	0.9853	0.9781	0.9817	137	0.9280	0.9397	0.9338	0.9859
0.0292	26.0	2496	0.0471	0.89	0.9468	0.9175	94	0.9212	0.9102	0.9157	167	0.9853	0.9781	0.9817	137	0.9352	0.9422	0.9387	0.9865
0.0279	27.0	2592	0.0479	0.8812	0.9468	0.9128	94	0.9068	0.8743	0.8902	167	0.9853	0.9781	0.9817	137	0.9271	0.9271	0.9271	0.9862
0.028	28.0	2688	0.0530	0.8491	0.9574	0.9	94	0.9304	0.8802	0.9046	167	0.9781	0.9781	0.9781	137	0.9252	0.9322	0.9287	0.9859
0.0266	29.0	2784	0.0534	0.8738	0.9574	0.9137	94	0.9367	0.8862	0.9108	167	0.9853	0.9781	0.9817	137	0.9370	0.9347	0.9358	0.9870
0.0247	30.0	2880	0.0493	0.8911	0.9574	0.9231	94	0.9152	0.9042	0.9096	167	0.9854	0.9854	0.9854	137	0.9330	0.9447	0.9388	0.9876
0.0232	31.0	2976	0.0528	0.9082	0.9468	0.9271	94	0.9207	0.9042	0.9124	167	0.9853	0.9781	0.9817	137	0.9397	0.9397	0.9397	0.9876
0.0249	32.0	3072	0.0561	0.8990	0.9468	0.9223	94	0.9053	0.9162	0.9107	167	0.9853	0.9781	0.9817	137	0.9307	0.9447	0.9377	0.9859
0.0235	33.0	3168	0.0554	0.9082	0.9468	0.9271	94	0.9379	0.9042	0.9207	167	0.9926	0.9781	0.9853	137	0.9492	0.9397	0.9444	0.9878
0.0226	34.0	3264	0.0601	0.8725	0.9468	0.9082	94	0.925	0.8862	0.9052	167	0.9779	0.9708	0.9744	137	0.9296	0.9296	0.9296	0.9862
0.0216	35.0	3360	0.0611	0.8571	0.9574	0.9045	94	0.9423	0.8802	0.9102	167	0.9781	0.9781	0.9781	137	0.9322	0.9322	0.9322	0.9859
0.0211	36.0	3456	0.0548	0.8476	0.9468	0.8945	94	0.9610	0.8862	0.9221	167	0.9779	0.9708	0.9744	137	0.9367	0.9296	0.9332	0.9873
0.0209	37.0	3552	0.0531	0.8558	0.9468	0.8990	94	0.9367	0.8862	0.9108	167	0.9926	0.9854	0.9890	137	0.9347	0.9347	0.9347	0.9867
0.0178	38.0	3648	0.0520	0.89	0.9468	0.9175	94	0.9321	0.9042	0.9179	167	0.9853	0.9781	0.9817	137	0.9397	0.9397	0.9397	0.9881
0.019	39.0	3744	0.0580	0.8654	0.9574	0.9091	94	0.9545	0.8802	0.9159	167	0.9926	0.9854	0.9890	137	0.9442	0.9347	0.9394	0.9876
0.0182	40.0	3840	0.0594	0.8585	0.9681	0.91	94	0.9419	0.8743	0.9068	167	0.9779	0.9708	0.9744	137	0.9320	0.9296	0.9308	0.9867
0.0175	41.0	3936	0.0499	0.8922	0.9681	0.9286	94	0.9325	0.9102	0.9212	167	0.9926	0.9854	0.9890	137	0.9426	0.9497	0.9462	0.9884
0.017	42.0	4032	0.0531	0.89	0.9468	0.9175	94	0.9259	0.8982	0.9119	167	0.9779	0.9708	0.9744	137	0.9347	0.9347	0.9347	0.9881
0.016	43.0	4128	0.0585	0.8738	0.9574	0.9137	94	0.9321	0.9042	0.9179	167	0.9853	0.9781	0.9817	137	0.9352	0.9422	0.9387	0.9867
0.0176	44.0	4224	0.0629	0.8654	0.9574	0.9091	94	0.9241	0.8743	0.8985	167	0.9926	0.9781	0.9853	137	0.9320	0.9296	0.9308	0.9856
0.0183	45.0	4320	0.0527	0.8990	0.9468	0.9223	94	0.9193	0.8862	0.9024	167	0.9778	0.9635	0.9706	137	0.9342	0.9271	0.9306	0.9867
0.0154	46.0	4416	0.0611	0.8558	0.9468	0.8990	94	0.9481	0.8743	0.9097	167	0.9778	0.9635	0.9706	137	0.9338	0.9221	0.9279	0.9865
0.0133	47.0	4512	0.0661	0.8725	0.9468	0.9082	94	0.8982	0.8982	0.8982	167	0.9926	0.9781	0.9853	137	0.9233	0.9372	0.9302	0.9865
0.0153	48.0	4608	0.0627	0.8641	0.9468	0.9036	94	0.9125	0.8743	0.8930	167	0.9853	0.9781	0.9817	137	0.9248	0.9271	0.9260	0.9865
0.0152	49.0	4704	0.0618	0.8641	0.9468	0.9036	94	0.9304	0.8802	0.9046	167	0.9852	0.9708	0.9779	137	0.9318	0.9271	0.9295	0.9867
0.0139	50.0	4800	0.0601	0.8911	0.9574	0.9231	94	0.9371	0.8922	0.9141	167	0.9706	0.9635	0.9670	137	0.9369	0.9322	0.9345	0.9876
0.0127	51.0	4896	0.0601	0.8812	0.9468	0.9128	94	0.9193	0.8862	0.9024	167	0.9779	0.9708	0.9744	137	0.9296	0.9296	0.9296	0.9873
0.0121	52.0	4992	0.0666	0.8990	0.9468	0.9223	94	0.9259	0.8982	0.9119	167	0.9779	0.9708	0.9744	137	0.9370	0.9347	0.9358	0.9876
0.0126	53.0	5088	0.0586	0.9	0.9574	0.9278	94	0.9259	0.8982	0.9119	167	0.9853	0.9781	0.9817	137	0.9397	0.9397	0.9397	0.9878
0.0124	54.0	5184	0.0609	0.9462	0.9362	0.9412	94	0.9281	0.9281	0.9281	167	0.9708	0.9708	0.9708	137	0.9471	0.9447	0.9459	0.9887
0.0131	55.0	5280	0.0614	0.9082	0.9468	0.9271	94	0.9317	0.8982	0.9146	167	0.9853	0.9781	0.9817	137	0.9443	0.9372	0.9407	0.9881
0.013	56.0	5376	0.0632	0.9091	0.9574	0.9326	94	0.9325	0.9102	0.9212	167	0.9779	0.9708	0.9744	137	0.9422	0.9422	0.9422	0.9884
0.0119	57.0	5472	0.0645	0.8824	0.9574	0.9184	94	0.9146	0.8982	0.9063	167	0.9779	0.9708	0.9744	137	0.9279	0.9372	0.9325	0.9865
0.0121	58.0	5568	0.0631	0.8725	0.9468	0.9082	94	0.925	0.8862	0.9052	167	0.9853	0.9781	0.9817	137	0.9322	0.9322	0.9322	0.9873
0.0109	59.0	5664	0.0638	0.8990	0.9468	0.9223	94	0.9375	0.8982	0.9174	167	0.9779	0.9708	0.9744	137	0.9418	0.9347	0.9382	0.9878
0.0117	60.0	5760	0.0665	0.8812	0.9468	0.9128	94	0.9371	0.8922	0.9141	167	0.9638	0.9708	0.9673	137	0.9322	0.9322	0.9322	0.9862
0.01	61.0	5856	0.0647	0.8824	0.9574	0.9184	94	0.9141	0.8922	0.9030	167	0.9708	0.9708	0.9708	137	0.9254	0.9347	0.93	0.9867
0.0108	62.0	5952	0.0601	0.9	0.9574	0.9278	94	0.9317	0.8982	0.9146	167	0.9779	0.9708	0.9744	137	0.9395	0.9372	0.9384	0.9876
0.0109	63.0	6048	0.0592	0.8990	0.9468	0.9223	94	0.9554	0.8982	0.9259	167	0.9853	0.9781	0.9817	137	0.9515	0.9372	0.9443	0.9890
0.0101	64.0	6144	0.0609	0.8725	0.9468	0.9082	94	0.9212	0.9102	0.9157	167	0.9779	0.9708	0.9744	137	0.9280	0.9397	0.9338	0.9867
0.0115	65.0	6240	0.0620	0.8725	0.9468	0.9082	94	0.9487	0.8862	0.9164	167	0.9779	0.9708	0.9744	137	0.9391	0.9296	0.9343	0.9870
0.0093	66.0	6336	0.0619	0.89	0.9468	0.9175	94	0.9152	0.9042	0.9096	167	0.9779	0.9708	0.9744	137	0.9302	0.9372	0.9337	0.9870
0.0105	67.0	6432	0.0596	0.8990	0.9468	0.9223	94	0.9434	0.8982	0.9202	167	0.9779	0.9708	0.9744	137	0.9442	0.9347	0.9394	0.9878
0.0094	68.0	6528	0.0608	0.9091	0.9574	0.9326	94	0.9437	0.9042	0.9235	167	0.9853	0.9781	0.9817	137	0.9494	0.9422	0.9458	0.9887
0.0096	69.0	6624	0.0638	0.8990	0.9468	0.9223	94	0.9618	0.9042	0.9321	167	0.9778	0.9635	0.9706	137	0.9514	0.9347	0.9430	0.9884
0.0089	70.0	6720	0.0630	0.8990	0.9468	0.9223	94	0.9679	0.9042	0.9350	167	0.9778	0.9635	0.9706	137	0.9538	0.9347	0.9442	0.9887
0.0097	71.0	6816	0.0628	0.9	0.9574	0.9278	94	0.9264	0.9042	0.9152	167	0.9779	0.9708	0.9744	137	0.9373	0.9397	0.9385	0.9878
0.0092	72.0	6912	0.0650	0.8812	0.9468	0.9128	94	0.9430	0.8922	0.9169	167	0.9779	0.9708	0.9744	137	0.9392	0.9322	0.9357	0.9873
0.0089	73.0	7008	0.0663	0.8990	0.9468	0.9223	94	0.9321	0.9042	0.9179	167	0.9706	0.9635	0.9670	137	0.9370	0.9347	0.9358	0.9878
0.0088	74.0	7104	0.0663	0.89	0.9468	0.9175	94	0.9259	0.8982	0.9119	167	0.9706	0.9635	0.9670	137	0.9322	0.9322	0.9322	0.9876
0.0076	75.0	7200	0.0646	0.9	0.9574	0.9278	94	0.9434	0.8982	0.9202	167	0.9779	0.9708	0.9744	137	0.9443	0.9372	0.9407	0.9884
0.0084	76.0	7296	0.0634	0.89	0.9468	0.9175	94	0.9379	0.9042	0.9207	167	0.9779	0.9708	0.9744	137	0.9395	0.9372	0.9384	0.9884
0.0079	77.0	7392	0.0647	0.9	0.9574	0.9278	94	0.9259	0.8982	0.9119	167	0.9706	0.9635	0.9670	137	0.9347	0.9347	0.9347	0.9878
0.0078	78.0	7488	0.0669	0.9082	0.9468	0.9271	94	0.9325	0.9102	0.9212	167	0.9706	0.9635	0.9670	137	0.9395	0.9372	0.9384	0.9881
0.0082	79.0	7584	0.0679	0.8812	0.9468	0.9128	94	0.9313	0.8922	0.9113	167	0.9706	0.9635	0.9670	137	0.9320	0.9296	0.9308	0.9870
0.0075	80.0	7680	0.0651	0.9091	0.9574	0.9326	94	0.9152	0.9042	0.9096	167	0.9779	0.9708	0.9744	137	0.935	0.9397	0.9373	0.9884
0.0086	81.0	7776	0.0650	0.9	0.9574	0.9278	94	0.9202	0.8982	0.9091	167	0.9779	0.9708	0.9744	137	0.9348	0.9372	0.9360	0.9873
0.0064	82.0	7872	0.0652	0.9091	0.9574	0.9326	94	0.9321	0.9042	0.9179	167	0.9779	0.9708	0.9744	137	0.9421	0.9397	0.9409	0.9881
0.006	83.0	7968	0.0676	0.9091	0.9574	0.9326	94	0.9264	0.9042	0.9152	167	0.9779	0.9708	0.9744	137	0.9397	0.9397	0.9397	0.9884
0.0079	84.0	8064	0.0677	0.9091	0.9574	0.9326	94	0.9268	0.9102	0.9184	167	0.9706	0.9635	0.9670	137	0.9373	0.9397	0.9385	0.9878
0.0074	85.0	8160	0.0699	0.9082	0.9468	0.9271	94	0.9321	0.9042	0.9179	167	0.9778	0.9635	0.9706	137	0.9418	0.9347	0.9382	0.9878
0.0084	86.0	8256	0.0696	0.9	0.9574	0.9278	94	0.9202	0.8982	0.9091	167	0.9779	0.9708	0.9744	137	0.9348	0.9372	0.9360	0.9878
0.007	87.0	8352	0.0680	0.9	0.9574	0.9278	94	0.9259	0.8982	0.9119	167	0.9779	0.9708	0.9744	137	0.9372	0.9372	0.9372	0.9878
0.0069	88.0	8448	0.0665	0.8911	0.9574	0.9231	94	0.9430	0.8922	0.9169	167	0.9779	0.9708	0.9744	137	0.9418	0.9347	0.9382	0.9884
0.0066	89.0	8544	0.0673	0.8911	0.9574	0.9231	94	0.925	0.8862	0.9052	167	0.9853	0.9781	0.9817	137	0.9370	0.9347	0.9358	0.9878
0.0072	90.0	8640	0.0687	0.8911	0.9574	0.9231	94	0.9487	0.8862	0.9164	167	0.9779	0.9708	0.9744	137	0.9440	0.9322	0.9381	0.9878
0.0067	91.0	8736	0.0693	0.8824	0.9574	0.9184	94	0.9255	0.8922	0.9085	167	0.9706	0.9635	0.9670	137	0.9298	0.9322	0.9310	0.9873
0.0064	92.0	8832	0.0697	0.9	0.9574	0.9278	94	0.9321	0.9042	0.9179	167	0.9706	0.9635	0.9670	137	0.9372	0.9372	0.9372	0.9881
0.007	93.0	8928	0.0683	0.9	0.9574	0.9278	94	0.9437	0.9042	0.9235	167	0.9779	0.9708	0.9744	137	0.9444	0.9397	0.9421	0.9890
0.0061	94.0	9024	0.0676	0.9091	0.9574	0.9326	94	0.9325	0.9102	0.9212	167	0.9706	0.9635	0.9670	137	0.9397	0.9397	0.9397	0.9884
0.0066	95.0	9120	0.0701	0.8824	0.9574	0.9184	94	0.9430	0.8922	0.9169	167	0.9706	0.9635	0.9670	137	0.9369	0.9322	0.9345	0.9881
0.0052	96.0	9216	0.0689	0.9	0.9574	0.9278	94	0.9379	0.9042	0.9207	167	0.9706	0.9635	0.9670	137	0.9395	0.9372	0.9384	0.9881
0.0052	97.0	9312	0.0702	0.8911	0.9574	0.9231	94	0.9434	0.8982	0.9202	167	0.9706	0.9635	0.9670	137	0.9394	0.9347	0.9370	0.9884
0.0073	98.0	9408	0.0692	0.9	0.9574	0.9278	94	0.9379	0.9042	0.9207	167	0.9706	0.9635	0.9670	137	0.9395	0.9372	0.9384	0.9881
0.0052	99.0	9504	0.0690	0.9	0.9574	0.9278	94	0.9379	0.9042	0.9207	167	0.9706	0.9635	0.9670	137	0.9395	0.9372	0.9384	0.9881
0.0063	100.0	9600	0.0690	0.9	0.9574	0.9278	94	0.9379	0.9042	0.9207	167	0.9706	0.9635	0.9670	137	0.9395	0.9372	0.9384	0.9881

Framework versions

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