nerui-pt-pl20-0

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: 0.0562
• Location Precision: 0.9
• Location Recall: 0.9574
• Location F1: 0.9278
• Location Number: 94
• Organization Precision: 0.9268
• Organization Recall: 0.9102
• Organization F1: 0.9184
• Organization Number: 167
• Person Precision: 0.9926
• Person Recall: 0.9854
• Person F1: 0.9890
• Person Number: 137
• Overall Precision: 0.9425
• Overall Recall: 0.9472
• Overall F1: 0.9449
• Overall Accuracy: 0.9876

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
0.8717	1.0	96	0.4085	0.0	0.0	0.0	94	0.2308	0.2156	0.2229	167	0.2595	0.3504	0.2981	137	0.2456	0.2111	0.2270	0.8638
0.3803	2.0	192	0.2545	0.3913	0.2872	0.3313	94	0.4693	0.6407	0.5418	167	0.6034	0.7883	0.6835	137	0.5084	0.6080	0.5538	0.9238
0.204	3.0	288	0.1028	0.8041	0.8298	0.8168	94	0.7487	0.8383	0.7910	167	0.9714	0.9927	0.9819	137	0.8349	0.8894	0.8613	0.9702
0.1305	4.0	384	0.0795	0.8447	0.9255	0.8832	94	0.8068	0.8503	0.8280	167	0.9645	0.9927	0.9784	137	0.8690	0.9171	0.8924	0.9738
0.1104	5.0	480	0.0698	0.8131	0.9255	0.8657	94	0.8535	0.8024	0.8272	167	0.9855	0.9927	0.9891	137	0.8881	0.8970	0.8925	0.9782
0.098	6.0	576	0.0536	0.8476	0.9468	0.8945	94	0.8690	0.8743	0.8716	167	0.9783	0.9854	0.9818	137	0.9002	0.9296	0.9147	0.9820
0.0876	7.0	672	0.0461	0.9010	0.9681	0.9333	94	0.8636	0.9102	0.8863	167	0.9926	0.9854	0.9890	137	0.9153	0.9497	0.9322	0.9851
0.0784	8.0	768	0.0440	0.8911	0.9574	0.9231	94	0.8795	0.8743	0.8769	167	0.9854	0.9854	0.9854	137	0.9183	0.9322	0.9252	0.9859
0.0721	9.0	864	0.0417	0.8364	0.9787	0.9020	94	0.9152	0.9042	0.9096	167	0.9926	0.9854	0.9890	137	0.9197	0.9497	0.9345	0.9854
0.0659	10.0	960	0.0440	0.8788	0.9255	0.9016	94	0.8791	0.9581	0.9169	167	0.9854	0.9854	0.9854	137	0.9139	0.9598	0.9363	0.9856
0.063	11.0	1056	0.0420	0.8288	0.9787	0.8976	94	0.9080	0.8862	0.8970	167	0.9926	0.9781	0.9853	137	0.9144	0.9397	0.9269	0.9845
0.0583	12.0	1152	0.0463	0.8529	0.9255	0.8878	94	0.8929	0.8982	0.8955	167	1.0	0.9854	0.9926	137	0.9185	0.9347	0.9265	0.9845
0.0562	13.0	1248	0.0454	0.87	0.9255	0.8969	94	0.8857	0.9281	0.9064	167	0.9926	0.9854	0.9890	137	0.9173	0.9472	0.9320	0.9840
0.0528	14.0	1344	0.0391	0.8365	0.9255	0.8788	94	0.8994	0.9102	0.9048	167	0.9927	0.9927	0.9927	137	0.9146	0.9422	0.9282	0.9867
0.048	15.0	1440	0.0409	0.8627	0.9362	0.8980	94	0.8895	0.9162	0.9027	167	0.9853	0.9781	0.9817	137	0.9146	0.9422	0.9282	0.9854
0.0464	16.0	1536	0.0360	0.8911	0.9574	0.9231	94	0.9329	0.9162	0.9245	167	1.0	0.9854	0.9926	137	0.945	0.9497	0.9474	0.9878
0.0466	17.0	1632	0.0425	0.8491	0.9574	0.9	94	0.9273	0.9162	0.9217	167	1.0	0.9781	0.9889	137	0.9309	0.9472	0.9390	0.9867
0.041	18.0	1728	0.0423	0.8333	0.9574	0.8911	94	0.9474	0.8623	0.9028	167	1.0	0.9854	0.9926	137	0.9342	0.9271	0.9306	0.9865
0.0423	19.0	1824	0.0420	0.8738	0.9574	0.9137	94	0.9141	0.8922	0.9030	167	1.0	0.9854	0.9926	137	0.9327	0.9397	0.9362	0.9856
0.0385	20.0	1920	0.0412	0.8505	0.9681	0.9055	94	0.9130	0.8802	0.8963	167	0.9926	0.9854	0.9890	137	0.9233	0.9372	0.9302	0.9854
0.0372	21.0	2016	0.0327	0.91	0.9681	0.9381	94	0.9286	0.9341	0.9313	167	0.9926	0.9854	0.9890	137	0.9455	0.9598	0.9526	0.9890
0.0336	22.0	2112	0.0359	0.9010	0.9681	0.9333	94	0.9186	0.9461	0.9322	167	0.9926	0.9854	0.9890	137	0.9389	0.9648	0.9517	0.9876
0.0345	23.0	2208	0.0414	0.8571	0.9574	0.9045	94	0.9375	0.8982	0.9174	167	1.0	0.9854	0.9926	137	0.9375	0.9422	0.9398	0.9870
0.0342	24.0	2304	0.0430	0.8911	0.9574	0.9231	94	0.925	0.8862	0.9052	167	0.9926	0.9781	0.9853	137	0.9394	0.9347	0.9370	0.9865
0.0315	25.0	2400	0.0396	0.9192	0.9681	0.9430	94	0.9136	0.8862	0.8997	167	0.9781	0.9781	0.9781	137	0.9372	0.9372	0.9372	0.9865
0.0306	26.0	2496	0.0405	0.8738	0.9574	0.9137	94	0.9202	0.8982	0.9091	167	0.9926	0.9854	0.9890	137	0.9328	0.9422	0.9375	0.9865
0.0302	27.0	2592	0.0496	0.8627	0.9362	0.8980	94	0.9295	0.8683	0.8978	167	1.0	0.9854	0.9926	137	0.9364	0.9246	0.9305	0.9865
0.0287	28.0	2688	0.0392	0.8641	0.9468	0.9036	94	0.9130	0.8802	0.8963	167	0.9926	0.9781	0.9853	137	0.9273	0.9296	0.9285	0.9859
0.0314	29.0	2784	0.0426	0.8654	0.9574	0.9091	94	0.9152	0.9042	0.9096	167	1.0	0.9781	0.9889	137	0.9305	0.9422	0.9363	0.9870
0.0259	30.0	2880	0.0466	0.9	0.9574	0.9278	94	0.9152	0.9042	0.9096	167	0.9926	0.9854	0.9890	137	0.9377	0.9447	0.9412	0.9862
0.0285	31.0	2976	0.0450	0.8990	0.9468	0.9223	94	0.9273	0.9162	0.9217	167	0.9781	0.9781	0.9781	137	0.9377	0.9447	0.9412	0.9862
0.0272	32.0	3072	0.0547	0.8396	0.9468	0.89	94	0.9042	0.9042	0.9042	167	1.0	0.9854	0.9926	137	0.9191	0.9422	0.9305	0.9837
0.0262	33.0	3168	0.0352	0.88	0.9362	0.9072	94	0.9277	0.9222	0.9249	167	0.9779	0.9708	0.9744	137	0.9328	0.9422	0.9375	0.9876
0.0255	34.0	3264	0.0422	0.8980	0.9362	0.9167	94	0.9198	0.8922	0.9058	167	0.9640	0.9781	0.9710	137	0.9298	0.9322	0.9310	0.9854
0.024	35.0	3360	0.0519	0.8505	0.9681	0.9055	94	0.9241	0.8743	0.8985	167	0.9854	0.9854	0.9854	137	0.9254	0.9347	0.93	0.9848
0.0223	36.0	3456	0.0559	0.8738	0.9574	0.9137	94	0.9375	0.8982	0.9174	167	0.9854	0.9854	0.9854	137	0.9375	0.9422	0.9398	0.9856
0.0213	37.0	3552	0.0485	0.8627	0.9362	0.8980	94	0.9042	0.9042	0.9042	167	0.9926	0.9854	0.9890	137	0.9235	0.9397	0.9315	0.9848
0.0221	38.0	3648	0.0481	0.9091	0.9574	0.9326	94	0.9112	0.9222	0.9167	167	0.9926	0.9781	0.9853	137	0.9380	0.9497	0.9438	0.9870
0.0217	39.0	3744	0.0462	0.875	0.9681	0.9192	94	0.9152	0.9042	0.9096	167	0.9926	0.9854	0.9890	137	0.9309	0.9472	0.9390	0.9859
0.0243	40.0	3840	0.0416	0.8932	0.9787	0.9340	94	0.9217	0.9162	0.9189	167	0.9853	0.9781	0.9817	137	0.9358	0.9523	0.9440	0.9876
0.0202	41.0	3936	0.0496	0.8725	0.9468	0.9082	94	0.9222	0.9222	0.9222	167	1.0	0.9854	0.9926	137	0.9356	0.9497	0.9426	0.9862
0.0191	42.0	4032	0.0408	0.8846	0.9787	0.9293	94	0.9207	0.9042	0.9124	167	0.9926	0.9854	0.9890	137	0.9356	0.9497	0.9426	0.9881
0.0191	43.0	4128	0.0425	0.875	0.9681	0.9192	94	0.9317	0.8982	0.9146	167	0.9926	0.9854	0.9890	137	0.9377	0.9447	0.9412	0.9873
0.0187	44.0	4224	0.0535	0.8411	0.9574	0.8955	94	0.9182	0.8743	0.8957	167	1.0	0.9854	0.9926	137	0.9252	0.9322	0.9287	0.9851
0.0189	45.0	4320	0.0353	0.89	0.9468	0.9175	94	0.9337	0.9281	0.9309	167	0.9926	0.9854	0.9890	137	0.9428	0.9523	0.9475	0.9895
0.0194	46.0	4416	0.0437	0.9010	0.9681	0.9333	94	0.9317	0.8982	0.9146	167	0.9926	0.9781	0.9853	137	0.9446	0.9422	0.9434	0.9881
0.0168	47.0	4512	0.0428	0.9010	0.9681	0.9333	94	0.9006	0.9222	0.9112	167	0.9926	0.9781	0.9853	137	0.9312	0.9523	0.9416	0.9878
0.0149	48.0	4608	0.0447	0.89	0.9468	0.9175	94	0.9268	0.9102	0.9184	167	0.9853	0.9781	0.9817	137	0.9375	0.9422	0.9398	0.9873
0.0167	49.0	4704	0.0453	0.8679	0.9787	0.9200	94	0.9444	0.9162	0.9301	167	1.0	0.9854	0.9926	137	0.9429	0.9548	0.9488	0.9884
0.0173	50.0	4800	0.0481	0.8835	0.9681	0.9239	94	0.9557	0.9042	0.9292	167	0.9854	0.9854	0.9854	137	0.9472	0.9472	0.9472	0.9876
0.0171	51.0	4896	0.0443	0.9	0.9574	0.9278	94	0.9371	0.8922	0.9141	167	0.9781	0.9781	0.9781	137	0.9419	0.9372	0.9395	0.9870
0.016	52.0	4992	0.0398	0.875	0.9681	0.9192	94	0.8988	0.9042	0.9015	167	0.9779	0.9708	0.9744	137	0.9191	0.9422	0.9305	0.9870
0.0163	53.0	5088	0.0472	0.8667	0.9681	0.9146	94	0.9371	0.8922	0.9141	167	0.9854	0.9854	0.9854	137	0.9352	0.9422	0.9387	0.9873
0.0147	54.0	5184	0.0444	0.9029	0.9894	0.9442	94	0.9390	0.9222	0.9305	167	0.9926	0.9854	0.9890	137	0.9479	0.9598	0.9538	0.9881
0.0143	55.0	5280	0.0496	0.8835	0.9681	0.9239	94	0.9096	0.9042	0.9069	167	0.9781	0.9781	0.9781	137	0.9261	0.9447	0.9353	0.9867
0.0146	56.0	5376	0.0445	0.9192	0.9681	0.9430	94	0.9321	0.9042	0.9179	167	0.9926	0.9854	0.9890	137	0.9496	0.9472	0.9484	0.9884
0.0129	57.0	5472	0.0445	0.9010	0.9681	0.9333	94	0.9557	0.9042	0.9292	167	0.9926	0.9854	0.9890	137	0.9544	0.9472	0.9508	0.9881
0.0139	58.0	5568	0.0445	0.8922	0.9681	0.9286	94	0.9490	0.8922	0.9198	167	0.9926	0.9854	0.9890	137	0.9494	0.9422	0.9458	0.9878
0.0136	59.0	5664	0.0508	0.8835	0.9681	0.9239	94	0.9329	0.9162	0.9245	167	0.9854	0.9854	0.9854	137	0.9381	0.9523	0.9451	0.9873
0.0119	60.0	5760	0.0508	0.8835	0.9681	0.9239	94	0.9162	0.9162	0.9162	167	0.9926	0.9781	0.9853	137	0.9333	0.9497	0.9415	0.9862
0.013	61.0	5856	0.0566	0.8889	0.9362	0.9119	94	0.9212	0.9102	0.9157	167	0.9926	0.9854	0.9890	137	0.9375	0.9422	0.9398	0.9859
0.0123	62.0	5952	0.0436	0.9167	0.9362	0.9263	94	0.9394	0.9281	0.9337	167	0.9854	0.9854	0.9854	137	0.9497	0.9497	0.9497	0.9892
0.0126	63.0	6048	0.0445	0.9192	0.9681	0.9430	94	0.9162	0.9162	0.9162	167	0.9926	0.9854	0.9890	137	0.9428	0.9523	0.9475	0.9873
0.0124	64.0	6144	0.0504	0.8762	0.9787	0.9246	94	0.9427	0.8862	0.9136	167	0.9926	0.9854	0.9890	137	0.9422	0.9422	0.9422	0.9878
0.0126	65.0	6240	0.0495	0.8911	0.9574	0.9231	94	0.9317	0.8982	0.9146	167	0.9926	0.9854	0.9890	137	0.9422	0.9422	0.9422	0.9870
0.013	66.0	6336	0.0517	0.8922	0.9681	0.9286	94	0.9308	0.8862	0.9080	167	0.9926	0.9854	0.9890	137	0.9421	0.9397	0.9409	0.9878
0.0112	67.0	6432	0.0500	0.8835	0.9681	0.9239	94	0.9487	0.8862	0.9164	167	0.9926	0.9854	0.9890	137	0.9468	0.9397	0.9433	0.9878
0.0103	68.0	6528	0.0515	0.9091	0.9574	0.9326	94	0.9281	0.9281	0.9281	167	0.9926	0.9854	0.9890	137	0.9453	0.9548	0.95	0.9878
0.0115	69.0	6624	0.0459	0.9010	0.9681	0.9333	94	0.9423	0.8802	0.9102	167	0.9926	0.9854	0.9890	137	0.9491	0.9372	0.9431	0.9878
0.0129	70.0	6720	0.0516	0.9184	0.9574	0.9375	94	0.9217	0.9162	0.9189	167	0.9926	0.9854	0.9890	137	0.945	0.9497	0.9474	0.9878
0.0105	71.0	6816	0.0486	0.8889	0.9362	0.9119	94	0.9207	0.9042	0.9124	167	0.9853	0.9781	0.9817	137	0.9348	0.9372	0.9360	0.9862
0.0098	72.0	6912	0.0553	0.875	0.9681	0.9192	94	0.9259	0.8982	0.9119	167	0.9779	0.9708	0.9744	137	0.9303	0.9397	0.9350	0.9862
0.0097	73.0	7008	0.0510	0.9	0.9574	0.9278	94	0.9497	0.9042	0.9264	167	0.9926	0.9854	0.9890	137	0.9519	0.9447	0.9483	0.9884
0.0109	74.0	7104	0.0485	0.91	0.9681	0.9381	94	0.9444	0.9162	0.9301	167	0.9781	0.9781	0.9781	137	0.9474	0.9497	0.9486	0.9884
0.0087	75.0	7200	0.0580	0.8738	0.9574	0.9137	94	0.9375	0.8982	0.9174	167	0.9926	0.9854	0.9890	137	0.9398	0.9422	0.9410	0.9867
0.0108	76.0	7296	0.0486	0.9010	0.9681	0.9333	94	0.9375	0.8982	0.9174	167	0.9926	0.9854	0.9890	137	0.9471	0.9447	0.9459	0.9878
0.0096	77.0	7392	0.0497	0.91	0.9681	0.9381	94	0.9434	0.8982	0.9202	167	0.9926	0.9854	0.9890	137	0.9519	0.9447	0.9483	0.9884
0.0091	78.0	7488	0.0498	0.9091	0.9574	0.9326	94	0.9375	0.8982	0.9174	167	0.9926	0.9854	0.9890	137	0.9494	0.9422	0.9458	0.9876
0.0106	79.0	7584	0.0502	0.8922	0.9681	0.9286	94	0.9390	0.9222	0.9305	167	0.9926	0.9854	0.9890	137	0.9453	0.9548	0.95	0.9881
0.0084	80.0	7680	0.0556	0.9	0.9574	0.9278	94	0.9255	0.8922	0.9085	167	0.9926	0.9854	0.9890	137	0.9421	0.9397	0.9409	0.9867
0.0096	81.0	7776	0.0591	0.8835	0.9681	0.9239	94	0.9146	0.8982	0.9063	167	0.9853	0.9781	0.9817	137	0.9305	0.9422	0.9363	0.9862
0.0087	82.0	7872	0.0520	0.9	0.9574	0.9278	94	0.9255	0.8922	0.9085	167	0.9926	0.9854	0.9890	137	0.9421	0.9397	0.9409	0.9867
0.0087	83.0	7968	0.0596	0.8824	0.9574	0.9184	94	0.9325	0.9102	0.9212	167	0.9926	0.9854	0.9890	137	0.9401	0.9472	0.9437	0.9870
0.0076	84.0	8064	0.0571	0.8911	0.9574	0.9231	94	0.9273	0.9162	0.9217	167	0.9926	0.9854	0.9890	137	0.9403	0.9497	0.9450	0.9870
0.0083	85.0	8160	0.0572	0.8835	0.9681	0.9239	94	0.9255	0.8922	0.9085	167	0.9926	0.9854	0.9890	137	0.9375	0.9422	0.9398	0.9867
0.0089	86.0	8256	0.0548	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	0.9873
0.0078	87.0	8352	0.0571	0.8911	0.9574	0.9231	94	0.9217	0.9162	0.9189	167	0.9926	0.9854	0.9890	137	0.9380	0.9497	0.9438	0.9870
0.0088	88.0	8448	0.0538	0.9	0.9574	0.9278	94	0.9212	0.9102	0.9157	167	0.9926	0.9854	0.9890	137	0.9401	0.9472	0.9437	0.9876
0.0079	89.0	8544	0.0579	0.8835	0.9681	0.9239	94	0.9383	0.9102	0.9240	167	0.9926	0.9854	0.9890	137	0.9426	0.9497	0.9462	0.9876
0.0094	90.0	8640	0.0556	0.9010	0.9681	0.9333	94	0.9325	0.9102	0.9212	167	0.9926	0.9854	0.9890	137	0.945	0.9497	0.9474	0.9878
0.0081	91.0	8736	0.0570	0.8980	0.9362	0.9167	94	0.9217	0.9162	0.9189	167	0.9926	0.9854	0.9890	137	0.94	0.9447	0.9424	0.9870
0.0073	92.0	8832	0.0574	0.8835	0.9681	0.9239	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.9378	0.9472	0.9425	0.9870
0.0076	93.0	8928	0.0575	0.8911	0.9574	0.9231	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.94	0.9447	0.9424	0.9873
0.0089	94.0	9024	0.0568	0.8911	0.9574	0.9231	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.94	0.9447	0.9424	0.9873
0.0081	95.0	9120	0.0586	0.8835	0.9681	0.9239	94	0.9321	0.9042	0.9179	167	0.9926	0.9854	0.9890	137	0.9401	0.9472	0.9437	0.9873
0.0077	96.0	9216	0.0569	0.89	0.9468	0.9175	94	0.9207	0.9042	0.9124	167	0.9926	0.9854	0.9890	137	0.9375	0.9422	0.9398	0.9870
0.0069	97.0	9312	0.0575	0.8911	0.9574	0.9231	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.94	0.9447	0.9424	0.9873
0.0086	98.0	9408	0.0583	0.8824	0.9574	0.9184	94	0.9264	0.9042	0.9152	167	0.9926	0.9854	0.9890	137	0.9377	0.9447	0.9412	0.9870
0.0073	99.0	9504	0.0564	0.9	0.9574	0.9278	94	0.9268	0.9102	0.9184	167	0.9926	0.9854	0.9890	137	0.9425	0.9472	0.9449	0.9876
0.0072	100.0	9600	0.0562	0.9	0.9574	0.9278	94	0.9268	0.9102	0.9184	167	0.9926	0.9854	0.9890	137	0.9425	0.9472	0.9449	0.9876

Framework versions

• Transformers 4.39.3
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.15.2