You can deploy this model and start earning money today!

apwic/
nerui-unipelt-3

Name: nerui-unipelt-3
Availability: InStock

tensorboard

generated_from_trainer

indolem/indobert-base-uncased

finetune

mit

Views

No views yet

nerui-unipelt-3

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: 0.0745
Location Precision: 0.8804
Location Recall: 0.9419
Location F1: 0.9101
Location Number: 86
Organization Precision: 0.9326
Organization Recall: 0.9326
Organization F1: 0.9326
Organization Number: 178
Person Precision: 0.9609
Person Recall: 0.9609
Person F1: 0.9609
Person Number: 128
Overall Precision: 0.9296
Overall Recall: 0.9439
Overall F1: 0.9367
Overall Accuracy: 0.9868

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
0.876	1.0	96	0.4974	0.0	0.0	0.0	86	0.4	0.0112	0.0219	178	0.0	0.0	0.0	128	0.2857	0.0051	0.0100	0.8440
0.3968	2.0	192	0.2417	0.3977	0.4070	0.4023	86	0.5330	0.5449	0.5389	178	0.6	0.7969	0.6846	128	0.5318	0.5969	0.5625	0.9277
0.1999	3.0	288	0.1151	0.7561	0.7209	0.7381	86	0.7202	0.7809	0.7493	178	0.9191	0.9766	0.9470	128	0.7932	0.8316	0.8120	0.9652
0.1248	4.0	384	0.0922	0.6759	0.8488	0.7526	86	0.8187	0.7865	0.8023	178	0.9685	0.9609	0.9647	128	0.8276	0.8571	0.8421	0.9706
0.1047	5.0	480	0.0657	0.77	0.8953	0.8280	86	0.8920	0.8820	0.8870	178	0.9615	0.9766	0.9690	128	0.8842	0.9158	0.8997	0.9798
0.0849	6.0	576	0.0716	0.6752	0.9186	0.7783	86	0.9156	0.7921	0.8494	178	0.9690	0.9766	0.9728	128	0.8625	0.8801	0.8712	0.9735
0.0754	7.0	672	0.0523	0.8387	0.9070	0.8715	86	0.8840	0.8989	0.8914	178	0.9766	0.9766	0.9766	128	0.9030	0.9260	0.9144	0.9843
0.0701	8.0	768	0.0519	0.8526	0.9419	0.8950	86	0.9106	0.9157	0.9132	178	0.9766	0.9766	0.9766	128	0.9179	0.9413	0.9295	0.9838
0.0619	9.0	864	0.0522	0.7810	0.9535	0.8586	86	0.9162	0.8596	0.8870	178	0.9690	0.9766	0.9728	128	0.8978	0.9184	0.9079	0.9819
0.0591	10.0	960	0.0523	0.8020	0.9419	0.8663	86	0.9096	0.9045	0.9070	178	0.9843	0.9766	0.9804	128	0.9062	0.9362	0.9210	0.9835
0.0529	11.0	1056	0.0497	0.8804	0.9419	0.9101	86	0.9257	0.9101	0.9178	178	0.9843	0.9766	0.9804	128	0.9340	0.9388	0.9364	0.9841
0.0491	12.0	1152	0.0482	0.8817	0.9535	0.9162	86	0.9006	0.9157	0.9081	178	0.9766	0.9766	0.9766	128	0.9204	0.9439	0.9320	0.9843
0.0441	13.0	1248	0.0492	0.8913	0.9535	0.9213	86	0.9467	0.8989	0.9222	178	0.9766	0.9766	0.9766	128	0.9434	0.9362	0.9398	0.9854
0.0401	14.0	1344	0.0526	0.8495	0.9186	0.8827	86	0.9455	0.8764	0.9096	178	0.9766	0.9766	0.9766	128	0.9326	0.9184	0.9254	0.9835
0.0392	15.0	1440	0.0466	0.8817	0.9535	0.9162	86	0.9278	0.9382	0.9330	178	0.9766	0.9766	0.9766	128	0.9327	0.9541	0.9433	0.9857
0.0366	16.0	1536	0.0465	0.8913	0.9535	0.9213	86	0.9483	0.9270	0.9375	178	0.9843	0.9766	0.9804	128	0.9466	0.9490	0.9478	0.9865
0.0342	17.0	1632	0.0503	0.9	0.9419	0.9205	86	0.9162	0.9213	0.9188	178	0.9688	0.9688	0.9688	128	0.9295	0.9413	0.9354	0.9835
0.0331	18.0	1728	0.0559	0.8723	0.9535	0.9111	86	0.9398	0.8764	0.9070	178	0.9690	0.9766	0.9728	128	0.9332	0.9260	0.9296	0.9843
0.0314	19.0	1824	0.0463	0.9186	0.9186	0.9186	86	0.9205	0.9101	0.9153	178	0.9766	0.9766	0.9766	128	0.9385	0.9337	0.9361	0.9860
0.0284	20.0	1920	0.0534	0.8723	0.9535	0.9111	86	0.9261	0.9157	0.9209	178	0.9843	0.9766	0.9804	128	0.9320	0.9439	0.9379	0.9846
0.0271	21.0	2016	0.0592	0.8723	0.9535	0.9111	86	0.9353	0.8933	0.9138	178	0.9688	0.9688	0.9688	128	0.9311	0.9311	0.9311	0.9838
0.0258	22.0	2112	0.0507	0.8557	0.9651	0.9071	86	0.9543	0.9382	0.9462	178	0.9766	0.9766	0.9766	128	0.9375	0.9566	0.9470	0.9873
0.0246	23.0	2208	0.0528	0.8617	0.9419	0.9000	86	0.9483	0.9270	0.9375	178	0.9766	0.9766	0.9766	128	0.9369	0.9464	0.9416	0.9857
0.0236	24.0	2304	0.0568	0.8632	0.9535	0.9061	86	0.9643	0.9101	0.9364	178	0.9766	0.9766	0.9766	128	0.9437	0.9413	0.9425	0.9841
0.0224	25.0	2400	0.0429	0.9205	0.9419	0.9310	86	0.9385	0.9438	0.9412	178	0.9766	0.9766	0.9766	128	0.9468	0.9541	0.9504	0.9889
0.0202	26.0	2496	0.0492	0.8913	0.9535	0.9213	86	0.9432	0.9326	0.9379	178	0.9690	0.9766	0.9728	128	0.9395	0.9515	0.9455	0.9876
0.0195	27.0	2592	0.0500	0.8696	0.9302	0.8989	86	0.9261	0.9157	0.9209	178	0.9609	0.9609	0.9609	128	0.9242	0.9337	0.9289	0.9860
0.0179	28.0	2688	0.0513	0.9	0.9419	0.9205	86	0.9385	0.9438	0.9412	178	0.9688	0.9688	0.9688	128	0.9395	0.9515	0.9455	0.9870
0.018	29.0	2784	0.0517	0.8913	0.9535	0.9213	86	0.9492	0.9438	0.9465	178	0.9688	0.9688	0.9688	128	0.9421	0.9541	0.9480	0.9881
0.0162	30.0	2880	0.0540	0.8710	0.9419	0.9050	86	0.9548	0.9494	0.9521	178	0.9609	0.9609	0.9609	128	0.9372	0.9515	0.9443	0.9868
0.0168	31.0	2976	0.0606	0.9011	0.9535	0.9266	86	0.9474	0.9101	0.9284	178	0.9688	0.9688	0.9688	128	0.9436	0.9388	0.9412	0.9862
0.0175	32.0	3072	0.0540	0.8778	0.9186	0.8977	86	0.9162	0.9213	0.9188	178	0.9609	0.9609	0.9609	128	0.9219	0.9337	0.9278	0.9852
0.0155	33.0	3168	0.0606	0.8925	0.9651	0.9274	86	0.9529	0.9101	0.9310	178	0.9609	0.9609	0.9609	128	0.9412	0.9388	0.9400	0.9857
0.0144	34.0	3264	0.0665	0.9130	0.9767	0.9438	86	0.9464	0.8933	0.9191	178	0.9688	0.9688	0.9688	128	0.9459	0.9362	0.9410	0.9857
0.0139	35.0	3360	0.0657	0.8632	0.9535	0.9061	86	0.9649	0.9270	0.9456	178	0.9609	0.9609	0.9609	128	0.9391	0.9439	0.9415	0.9865
0.0147	36.0	3456	0.0609	0.8925	0.9651	0.9274	86	0.9375	0.9270	0.9322	178	0.9688	0.9688	0.9688	128	0.9370	0.9490	0.9430	0.9862
0.0132	37.0	3552	0.0603	0.9091	0.9302	0.9195	86	0.9270	0.9270	0.9270	178	0.9609	0.9609	0.9609	128	0.9340	0.9388	0.9364	0.9857
0.0146	38.0	3648	0.0726	0.8469	0.9651	0.9022	86	0.9425	0.9213	0.9318	178	0.9766	0.9766	0.9766	128	0.93	0.9490	0.9394	0.9849
0.0124	39.0	3744	0.0662	0.8404	0.9186	0.8778	86	0.9213	0.9213	0.9213	178	0.9688	0.9688	0.9688	128	0.9175	0.9362	0.9268	0.9843
0.011	40.0	3840	0.0662	0.9101	0.9419	0.9257	86	0.9483	0.9270	0.9375	178	0.9609	0.9609	0.9609	128	0.9437	0.9413	0.9425	0.9865
0.0102	41.0	3936	0.0581	0.9213	0.9535	0.9371	86	0.9483	0.9270	0.9375	178	0.9688	0.9688	0.9688	128	0.9488	0.9464	0.9476	0.9887
0.0104	42.0	4032	0.0627	0.8791	0.9302	0.9040	86	0.9382	0.9382	0.9382	178	0.9688	0.9688	0.9688	128	0.9345	0.9464	0.9404	0.9862
0.009	43.0	4128	0.0637	0.9101	0.9419	0.9257	86	0.9261	0.9157	0.9209	178	0.9766	0.9766	0.9766	128	0.9389	0.9413	0.9401	0.9870
0.011	44.0	4224	0.0678	0.8830	0.9651	0.9222	86	0.9257	0.9101	0.9178	178	0.9766	0.9766	0.9766	128	0.9320	0.9439	0.9379	0.9857
0.0106	45.0	4320	0.0658	0.9195	0.9302	0.9249	86	0.9266	0.9213	0.9239	178	0.9688	0.9688	0.9688	128	0.9388	0.9388	0.9388	0.9857
0.0084	46.0	4416	0.0661	0.8438	0.9419	0.8901	86	0.9270	0.9270	0.9270	178	0.9766	0.9766	0.9766	128	0.9229	0.9464	0.9345	0.9857
0.0082	47.0	4512	0.0620	0.8791	0.9302	0.9040	86	0.9379	0.9326	0.9352	178	0.9609	0.9609	0.9609	128	0.9318	0.9413	0.9365	0.9868
0.0088	48.0	4608	0.0619	0.8989	0.9302	0.9143	86	0.9432	0.9326	0.9379	178	0.9688	0.9688	0.9688	128	0.9415	0.9439	0.9427	0.9879
0.0089	49.0	4704	0.0825	0.9	0.9419	0.9205	86	0.9425	0.9213	0.9318	178	0.9609	0.9609	0.9609	128	0.9388	0.9388	0.9388	0.9846
0.0077	50.0	4800	0.0769	0.9101	0.9419	0.9257	86	0.9477	0.9157	0.9314	178	0.9609	0.9609	0.9609	128	0.9434	0.9362	0.9398	0.9846
0.0072	51.0	4896	0.0768	0.9111	0.9535	0.9318	86	0.9474	0.9101	0.9284	178	0.9609	0.9609	0.9609	128	0.9434	0.9362	0.9398	0.9846
0.0068	52.0	4992	0.0711	0.8710	0.9419	0.9050	86	0.9429	0.9270	0.9348	178	0.9609	0.9609	0.9609	128	0.9318	0.9413	0.9365	0.9849
0.0071	53.0	5088	0.0648	0.9101	0.9419	0.9257	86	0.9066	0.9270	0.9167	178	0.9609	0.9609	0.9609	128	0.9248	0.9413	0.9330	0.9857
0.0073	54.0	5184	0.0678	0.8901	0.9419	0.9153	86	0.9266	0.9213	0.9239	178	0.9609	0.9609	0.9609	128	0.9293	0.9388	0.9340	0.9852
0.0066	55.0	5280	0.0677	0.8737	0.9651	0.9171	86	0.9314	0.9157	0.9235	178	0.9688	0.9688	0.9688	128	0.9296	0.9439	0.9367	0.9860
0.006	56.0	5376	0.0687	0.9	0.9419	0.9205	86	0.9278	0.9382	0.9330	178	0.9609	0.9609	0.9609	128	0.9322	0.9464	0.9392	0.9868
0.0069	57.0	5472	0.0694	0.9121	0.9651	0.9379	86	0.9227	0.9382	0.9304	178	0.9688	0.9688	0.9688	128	0.935	0.9541	0.9444	0.9876
0.0065	58.0	5568	0.0705	0.9101	0.9419	0.9257	86	0.9227	0.9382	0.9304	178	0.9609	0.9609	0.9609	128	0.9322	0.9464	0.9392	0.9879
0.0056	59.0	5664	0.0720	0.9	0.9419	0.9205	86	0.9364	0.9101	0.9231	178	0.9766	0.9766	0.9766	128	0.9412	0.9388	0.9400	0.9854
0.0063	60.0	5760	0.0713	0.9022	0.9651	0.9326	86	0.9371	0.9213	0.9292	178	0.9766	0.9766	0.9766	128	0.9418	0.9490	0.9454	0.9865
0.0051	61.0	5856	0.0827	0.9213	0.9535	0.9371	86	0.9527	0.9045	0.9280	178	0.9609	0.9609	0.9609	128	0.9482	0.9337	0.9409	0.9846
0.0053	62.0	5952	0.0748	0.9101	0.9419	0.9257	86	0.9318	0.9213	0.9266	178	0.9609	0.9609	0.9609	128	0.9364	0.9388	0.9376	0.9854
0.0059	63.0	6048	0.0703	0.9111	0.9535	0.9318	86	0.9326	0.9326	0.9326	178	0.9609	0.9609	0.9609	128	0.9369	0.9464	0.9416	0.9879
0.0051	64.0	6144	0.0734	0.8977	0.9186	0.9080	86	0.9314	0.9157	0.9235	178	0.9609	0.9609	0.9609	128	0.9335	0.9311	0.9323	0.9852
0.0055	65.0	6240	0.0747	0.8901	0.9419	0.9153	86	0.9368	0.9157	0.9261	178	0.9609	0.9609	0.9609	128	0.9338	0.9362	0.9350	0.9862
0.0042	66.0	6336	0.0749	0.8804	0.9419	0.9101	86	0.9261	0.9157	0.9209	178	0.9609	0.9609	0.9609	128	0.9268	0.9362	0.9315	0.9860
0.0048	67.0	6432	0.0713	0.8901	0.9419	0.9153	86	0.9218	0.9270	0.9244	178	0.9609	0.9609	0.9609	128	0.9271	0.9413	0.9342	0.9857
0.0051	68.0	6528	0.0804	0.9213	0.9535	0.9371	86	0.9529	0.9101	0.9310	178	0.9609	0.9609	0.9609	128	0.9483	0.9362	0.9422	0.9849
0.0066	69.0	6624	0.0728	0.8901	0.9419	0.9153	86	0.9218	0.9270	0.9244	178	0.9609	0.9609	0.9609	128	0.9271	0.9413	0.9342	0.9849
0.0049	70.0	6720	0.0695	0.8901	0.9419	0.9153	86	0.9218	0.9270	0.9244	178	0.9688	0.9688	0.9688	128	0.9296	0.9439	0.9367	0.9868
0.004	71.0	6816	0.0688	0.8989	0.9302	0.9143	86	0.9189	0.9551	0.9366	178	0.9609	0.9609	0.9609	128	0.9279	0.9515	0.9395	0.9868
0.0035	72.0	6912	0.0727	0.8913	0.9535	0.9213	86	0.9213	0.9213	0.9213	178	0.9766	0.9766	0.9766	128	0.9322	0.9464	0.9392	0.9860
0.0046	73.0	7008	0.0696	0.8817	0.9535	0.9162	86	0.9116	0.9270	0.9192	178	0.9766	0.9766	0.9766	128	0.9254	0.9490	0.9370	0.9860
0.0036	74.0	7104	0.0704	0.8817	0.9535	0.9162	86	0.9222	0.9326	0.9274	178	0.9766	0.9766	0.9766	128	0.9302	0.9515	0.9407	0.9868
0.0034	75.0	7200	0.0796	0.9213	0.9535	0.9371	86	0.9586	0.9101	0.9337	178	0.9688	0.9688	0.9688	128	0.9534	0.9388	0.9460	0.9852
0.0046	76.0	7296	0.0707	0.8901	0.9419	0.9153	86	0.9385	0.9438	0.9412	178	0.9688	0.9688	0.9688	128	0.9372	0.9515	0.9443	0.9879
0.003	77.0	7392	0.0729	0.9011	0.9535	0.9266	86	0.9266	0.9213	0.9239	178	0.9688	0.9688	0.9688	128	0.9343	0.9439	0.9391	0.9868
0.0033	78.0	7488	0.0742	0.9111	0.9535	0.9318	86	0.9419	0.9101	0.9257	178	0.9688	0.9688	0.9688	128	0.9436	0.9388	0.9412	0.9865
0.0035	79.0	7584	0.0728	0.8901	0.9419	0.9153	86	0.9056	0.9157	0.9106	178	0.9688	0.9688	0.9688	128	0.9223	0.9388	0.9305	0.9860
0.0037	80.0	7680	0.0774	0.8901	0.9419	0.9153	86	0.9425	0.9213	0.9318	178	0.9688	0.9688	0.9688	128	0.9389	0.9413	0.9401	0.9849
0.0035	81.0	7776	0.0759	0.9022	0.9651	0.9326	86	0.9480	0.9213	0.9345	178	0.9688	0.9688	0.9688	128	0.9440	0.9464	0.9452	0.9857
0.0037	82.0	7872	0.0711	0.8901	0.9419	0.9153	86	0.9213	0.9213	0.9213	178	0.9609	0.9609	0.9609	128	0.9270	0.9388	0.9328	0.9868
0.0034	83.0	7968	0.0737	0.9	0.9419	0.9205	86	0.9222	0.9326	0.9274	178	0.9609	0.9609	0.9609	128	0.9296	0.9439	0.9367	0.9868
0.0026	84.0	8064	0.0736	0.8901	0.9419	0.9153	86	0.9330	0.9382	0.9356	178	0.9609	0.9609	0.9609	128	0.9322	0.9464	0.9392	0.9876
0.0041	85.0	8160	0.0708	0.8989	0.9302	0.9143	86	0.9218	0.9270	0.9244	178	0.9609	0.9609	0.9609	128	0.9293	0.9388	0.9340	0.9873
0.0037	86.0	8256	0.0743	0.9	0.9419	0.9205	86	0.9375	0.9270	0.9322	178	0.9609	0.9609	0.9609	128	0.9365	0.9413	0.9389	0.9860
0.0038	87.0	8352	0.0698	0.9	0.9419	0.9205	86	0.9379	0.9326	0.9352	178	0.9609	0.9609	0.9609	128	0.9367	0.9439	0.9403	0.9876
0.003	88.0	8448	0.0752	0.9011	0.9535	0.9266	86	0.9270	0.9270	0.9270	178	0.9609	0.9609	0.9609	128	0.9320	0.9439	0.9379	0.9870
0.0027	89.0	8544	0.0747	0.8804	0.9419	0.9101	86	0.9330	0.9382	0.9356	178	0.9609	0.9609	0.9609	128	0.9298	0.9464	0.9381	0.9868
0.0028	90.0	8640	0.0741	0.8804	0.9419	0.9101	86	0.9379	0.9326	0.9352	178	0.9609	0.9609	0.9609	128	0.9320	0.9439	0.9379	0.9868
0.0027	91.0	8736	0.0747	0.8901	0.9419	0.9153	86	0.9382	0.9382	0.9382	178	0.9609	0.9609	0.9609	128	0.9345	0.9464	0.9404	0.9873
0.0024	92.0	8832	0.0731	0.9	0.9419	0.9205	86	0.9222	0.9326	0.9274	178	0.9609	0.9609	0.9609	128	0.9296	0.9439	0.9367	0.9873
0.0032	93.0	8928	0.0740	0.8817	0.9535	0.9162	86	0.9278	0.9382	0.9330	178	0.9688	0.9688	0.9688	128	0.9302	0.9515	0.9407	0.9879
0.0024	94.0	9024	0.0746	0.9	0.9419	0.9205	86	0.9218	0.9270	0.9244	178	0.9609	0.9609	0.9609	128	0.9295	0.9413	0.9354	0.9868
0.003	95.0	9120	0.0735	0.8817	0.9535	0.9162	86	0.9330	0.9382	0.9356	178	0.9688	0.9688	0.9688	128	0.9325	0.9515	0.9419	0.9876
0.0028	96.0	9216	0.0745	0.8901	0.9419	0.9153	86	0.9326	0.9326	0.9326	178	0.9609	0.9609	0.9609	128	0.9320	0.9439	0.9379	0.9868
0.0019	97.0	9312	0.0752	0.8804	0.9419	0.9101	86	0.9218	0.9270	0.9244	178	0.9609	0.9609	0.9609	128	0.9248	0.9413	0.9330	0.9862
0.0023	98.0	9408	0.0751	0.8804	0.9419	0.9101	86	0.9218	0.9270	0.9244	178	0.9609	0.9609	0.9609	128	0.9248	0.9413	0.9330	0.9862
0.0023	99.0	9504	0.0747	0.8817	0.9535	0.9162	86	0.9326	0.9326	0.9326	178	0.9688	0.9688	0.9688	128	0.9323	0.9490	0.9406	0.9870
0.0024	100.0	9600	0.0745	0.8804	0.9419	0.9101	86	0.9326	0.9326	0.9326	178	0.9609	0.9609	0.9609	128	0.9296	0.9439	0.9367	0.9868

Framework versions

Transformers 4.39.3
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.15.2

apwic/nerui-unipelt-3

nerui-unipelt-3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

apwic/
nerui-unipelt-3