nerui-lora-r8-1

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: 0.0379
• Location Precision: 0.9153
• Location Recall: 0.9310
• Location F1: 0.9231
• Location Number: 116
• Organization Precision: 0.9012
• Organization Recall: 0.9241
• Organization F1: 0.9125
• Organization Number: 158
• Person Precision: 0.984
• Person Recall: 0.9919
• Person F1: 0.9880
• Person Number: 124
• Overall Precision: 0.9309
• Overall Recall: 0.9472
• Overall F1: 0.9390
• 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
1.1502	1.0	96	0.6915	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
0.6681	2.0	192	0.5641	0.0	0.0	0.0	116	0.5	0.0063	0.0125	158	0.0	0.0	0.0	124	0.5	0.0025	0.005	0.8397
0.5591	3.0	288	0.4474	0.0	0.0	0.0	116	0.4286	0.0570	0.1006	158	0.2727	0.0484	0.0822	124	0.3333	0.0377	0.0677	0.8471
0.4414	4.0	384	0.3290	0.2692	0.0603	0.0986	116	0.3592	0.2342	0.2835	158	0.4071	0.4597	0.4318	124	0.3755	0.2538	0.3028	0.8847
0.3301	5.0	480	0.2424	0.4459	0.2845	0.3474	116	0.4874	0.6139	0.5434	158	0.5669	0.7177	0.6335	124	0.5093	0.5503	0.5290	0.9256
0.2536	6.0	576	0.1846	0.6372	0.6207	0.6288	116	0.6264	0.7215	0.6706	158	0.7347	0.8710	0.7970	124	0.6652	0.7387	0.7	0.9525
0.2029	7.0	672	0.1468	0.7328	0.7328	0.7328	116	0.6778	0.7722	0.7219	158	0.8676	0.9516	0.9077	124	0.7523	0.8166	0.7831	0.9629
0.1712	8.0	768	0.1217	0.7949	0.8017	0.7983	116	0.7356	0.8101	0.7711	158	0.9104	0.9839	0.9457	124	0.8071	0.8618	0.8335	0.9679
0.1504	9.0	864	0.1066	0.8220	0.8362	0.8291	116	0.7630	0.8354	0.7976	158	0.9173	0.9839	0.9494	124	0.8278	0.8819	0.8540	0.9717
0.1356	10.0	960	0.0944	0.8305	0.8448	0.8376	116	0.7917	0.8418	0.8160	158	0.9173	0.9839	0.9494	124	0.8425	0.8869	0.8641	0.9734
0.1276	11.0	1056	0.0848	0.8305	0.8448	0.8376	116	0.8084	0.8544	0.8308	158	0.9173	0.9839	0.9494	124	0.8493	0.8920	0.8701	0.9745
0.1202	12.0	1152	0.0797	0.8739	0.8966	0.8851	116	0.8313	0.8734	0.8519	158	0.9173	0.9839	0.9494	124	0.8708	0.9146	0.8922	0.9769
0.1131	13.0	1248	0.0725	0.8824	0.9052	0.8936	116	0.8274	0.8797	0.8528	158	0.9531	0.9839	0.9683	124	0.8819	0.9196	0.9004	0.9786
0.1074	14.0	1344	0.0678	0.8983	0.9138	0.9060	116	0.8625	0.8734	0.8679	158	0.9457	0.9839	0.9644	124	0.8993	0.9196	0.9093	0.9797
0.1046	15.0	1440	0.0671	0.8618	0.9138	0.8870	116	0.8383	0.8861	0.8615	158	0.9462	0.9919	0.9685	124	0.8786	0.9271	0.9022	0.9786
0.0992	16.0	1536	0.0648	0.8833	0.9138	0.8983	116	0.8393	0.8924	0.8650	158	0.9535	0.9919	0.9723	124	0.8873	0.9296	0.9080	0.9800
0.0972	17.0	1632	0.0611	0.9052	0.9052	0.9052	116	0.8805	0.8861	0.8833	158	0.9531	0.9839	0.9683	124	0.9107	0.9221	0.9164	0.9822
0.0908	18.0	1728	0.0583	0.8678	0.9052	0.8861	116	0.8720	0.9051	0.8882	158	0.9683	0.9839	0.976	124	0.9002	0.9296	0.9147	0.9822
0.089	19.0	1824	0.0568	0.8678	0.9052	0.8861	116	0.8805	0.8861	0.8833	158	0.9606	0.9839	0.9721	124	0.9017	0.9221	0.9118	0.9816
0.0872	20.0	1920	0.0591	0.8824	0.9052	0.8936	116	0.8462	0.9051	0.8746	158	0.9535	0.9919	0.9723	124	0.8897	0.9322	0.9104	0.9805
0.0863	21.0	2016	0.0565	0.8770	0.9224	0.8992	116	0.8421	0.9114	0.8754	158	0.9762	0.9919	0.9840	124	0.8926	0.9397	0.9155	0.9822
0.0834	22.0	2112	0.0545	0.8833	0.9138	0.8983	116	0.8471	0.9114	0.8780	158	0.9762	0.9919	0.9840	124	0.8966	0.9372	0.9165	0.9822
0.0795	23.0	2208	0.0511	0.8824	0.9052	0.8936	116	0.8667	0.9051	0.8854	158	0.9683	0.9839	0.976	124	0.9024	0.9296	0.9158	0.9835
0.0815	24.0	2304	0.0501	0.8898	0.9052	0.8974	116	0.8861	0.8861	0.8861	158	0.9762	0.9919	0.9840	124	0.9154	0.9246	0.92	0.9824
0.0764	25.0	2400	0.0491	0.8974	0.9052	0.9013	116	0.8727	0.9114	0.8916	158	0.9762	0.9919	0.9840	124	0.9118	0.9347	0.9231	0.9844
0.077	26.0	2496	0.0477	0.9052	0.9052	0.9052	116	0.8788	0.9177	0.8978	158	0.984	0.9919	0.9880	124	0.9187	0.9372	0.9279	0.9849
0.0749	27.0	2592	0.0504	0.9060	0.9138	0.9099	116	0.8855	0.9304	0.9074	158	0.9762	0.9919	0.9840	124	0.9193	0.9447	0.9318	0.9844
0.0728	28.0	2688	0.0490	0.8824	0.9052	0.8936	116	0.8667	0.9051	0.8854	158	0.984	0.9919	0.9880	124	0.9071	0.9322	0.9195	0.9841
0.0698	29.0	2784	0.0478	0.8824	0.9052	0.8936	116	0.8727	0.9114	0.8916	158	0.984	0.9919	0.9880	124	0.9095	0.9347	0.9219	0.9841
0.0694	30.0	2880	0.0466	0.9052	0.9052	0.9052	116	0.8683	0.9177	0.8923	158	0.9683	0.9839	0.976	124	0.9095	0.9347	0.9219	0.9846
0.0661	31.0	2976	0.0459	0.9060	0.9138	0.9099	116	0.8848	0.9241	0.9040	158	0.984	0.9919	0.9880	124	0.9214	0.9422	0.9317	0.9855
0.0672	32.0	3072	0.0454	0.8974	0.9052	0.9013	116	0.8659	0.8987	0.8820	158	0.984	0.9919	0.9880	124	0.9113	0.9296	0.9204	0.9849
0.0663	33.0	3168	0.0459	0.8974	0.9052	0.9013	116	0.8606	0.8987	0.8793	158	0.984	0.9919	0.9880	124	0.9091	0.9296	0.9193	0.9846
0.067	34.0	3264	0.0461	0.8824	0.9052	0.8936	116	0.8667	0.9051	0.8854	158	0.984	0.9919	0.9880	124	0.9071	0.9322	0.9195	0.9841
0.0628	35.0	3360	0.0449	0.9052	0.9052	0.9052	116	0.8675	0.9114	0.8889	158	0.984	0.9919	0.9880	124	0.9140	0.9347	0.9242	0.9852
0.0617	36.0	3456	0.0461	0.8992	0.9224	0.9106	116	0.8780	0.9114	0.8944	158	0.984	0.9919	0.9880	124	0.9167	0.9397	0.9280	0.9852
0.0617	37.0	3552	0.0432	0.8974	0.9052	0.9013	116	0.8788	0.9177	0.8978	158	0.984	0.9919	0.9880	124	0.9165	0.9372	0.9267	0.9855
0.0603	38.0	3648	0.0430	0.8992	0.9224	0.9106	116	0.8944	0.9114	0.9028	158	0.9683	0.9839	0.976	124	0.9187	0.9372	0.9279	0.9860
0.0617	39.0	3744	0.0413	0.8974	0.9052	0.9013	116	0.8727	0.9114	0.8916	158	0.984	0.9919	0.9880	124	0.9140	0.9347	0.9242	0.9852
0.0563	40.0	3840	0.0410	0.8983	0.9138	0.9060	116	0.8827	0.9051	0.8938	158	0.984	0.9919	0.9880	124	0.9185	0.9347	0.9265	0.9855
0.0579	41.0	3936	0.0427	0.9008	0.9397	0.9198	116	0.8938	0.9051	0.8994	158	0.984	0.9919	0.9880	124	0.9236	0.9422	0.9328	0.9857
0.0566	42.0	4032	0.0413	0.8926	0.9310	0.9114	116	0.8875	0.8987	0.8931	158	0.9683	0.9839	0.976	124	0.9140	0.9347	0.9242	0.9855
0.0578	43.0	4128	0.0422	0.9060	0.9138	0.9099	116	0.8944	0.9114	0.9028	158	0.9683	0.9839	0.976	124	0.9208	0.9347	0.9277	0.9860
0.0567	44.0	4224	0.0414	0.9068	0.9224	0.9145	116	0.9125	0.9241	0.9182	158	0.984	0.9919	0.9880	124	0.9330	0.9447	0.9388	0.9871
0.0568	45.0	4320	0.0400	0.8926	0.9310	0.9114	116	0.8994	0.9051	0.9022	158	0.9683	0.9839	0.976	124	0.9187	0.9372	0.9279	0.9860
0.053	46.0	4416	0.0409	0.9076	0.9310	0.9191	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9865
0.0536	47.0	4512	0.0408	0.9068	0.9224	0.9145	116	0.9018	0.9304	0.9159	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9865
0.0519	48.0	4608	0.0401	0.8917	0.9224	0.9068	116	0.8951	0.9177	0.9062	158	0.984	0.9919	0.9880	124	0.9214	0.9422	0.9317	0.9865
0.0539	49.0	4704	0.0401	0.9068	0.9224	0.9145	116	0.9125	0.9241	0.9182	158	0.984	0.9919	0.9880	124	0.9330	0.9447	0.9388	0.9865
0.0522	50.0	4800	0.0418	0.9008	0.9397	0.9198	116	0.9	0.9114	0.9057	158	0.984	0.9919	0.9880	124	0.9261	0.9447	0.9353	0.9865
0.0518	51.0	4896	0.0404	0.8992	0.9224	0.9106	116	0.9062	0.9177	0.9119	158	0.9683	0.9839	0.976	124	0.9235	0.9397	0.9315	0.9863
0.0503	52.0	4992	0.0393	0.9138	0.9138	0.9138	116	0.8916	0.9367	0.9136	158	0.984	0.9919	0.9880	124	0.9263	0.9472	0.9366	0.9868
0.0499	53.0	5088	0.0392	0.9237	0.9397	0.9316	116	0.8963	0.9304	0.9130	158	0.984	0.9919	0.9880	124	0.9312	0.9523	0.9416	0.9876
0.0498	54.0	5184	0.0393	0.9068	0.9224	0.9145	116	0.9018	0.9304	0.9159	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0492	55.0	5280	0.0390	0.9068	0.9224	0.9145	116	0.9018	0.9304	0.9159	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9874
0.0503	56.0	5376	0.0399	0.9237	0.9397	0.9316	116	0.9024	0.9367	0.9193	158	0.984	0.9919	0.9880	124	0.9337	0.9548	0.9441	0.9876
0.0491	57.0	5472	0.0408	0.9237	0.9397	0.9316	116	0.9024	0.9367	0.9193	158	0.984	0.9919	0.9880	124	0.9337	0.9548	0.9441	0.9876
0.0492	58.0	5568	0.0387	0.9237	0.9397	0.9316	116	0.9024	0.9367	0.9193	158	0.984	0.9919	0.9880	124	0.9337	0.9548	0.9441	0.9882
0.0477	59.0	5664	0.0390	0.9237	0.9397	0.9316	116	0.9136	0.9367	0.9250	158	0.984	0.9919	0.9880	124	0.9383	0.9548	0.9465	0.9882
0.0489	60.0	5760	0.0385	0.9244	0.9483	0.9362	116	0.9074	0.9304	0.9187	158	0.984	0.9919	0.9880	124	0.9360	0.9548	0.9453	0.9879
0.0446	61.0	5856	0.0391	0.9160	0.9397	0.9277	116	0.9177	0.9177	0.9177	158	0.984	0.9919	0.9880	124	0.9378	0.9472	0.9425	0.9865
0.0463	62.0	5952	0.0402	0.9237	0.9397	0.9316	116	0.9245	0.9304	0.9274	158	0.984	0.9919	0.9880	124	0.9428	0.9523	0.9475	0.9871
0.0482	63.0	6048	0.0401	0.9316	0.9397	0.9356	116	0.9130	0.9304	0.9216	158	0.984	0.9919	0.9880	124	0.9404	0.9523	0.9463	0.9868
0.0455	64.0	6144	0.0387	0.9068	0.9224	0.9145	116	0.9231	0.9114	0.9172	158	0.984	0.9919	0.9880	124	0.9373	0.9397	0.9385	0.9863
0.0432	65.0	6240	0.0392	0.9231	0.9310	0.9270	116	0.9125	0.9241	0.9182	158	0.984	0.9919	0.9880	124	0.9378	0.9472	0.9425	0.9865
0.0484	66.0	6336	0.0392	0.9153	0.9310	0.9231	116	0.9068	0.9241	0.9154	158	0.984	0.9919	0.9880	124	0.9332	0.9472	0.9401	0.9865
0.044	67.0	6432	0.0385	0.9153	0.9310	0.9231	116	0.9068	0.9241	0.9154	158	0.984	0.9919	0.9880	124	0.9332	0.9472	0.9401	0.9865
0.0425	68.0	6528	0.0386	0.9237	0.9397	0.9316	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9333	0.9497	0.9415	0.9871
0.044	69.0	6624	0.0381	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9865
0.0447	70.0	6720	0.0381	0.9153	0.9310	0.9231	116	0.9074	0.9304	0.9187	158	0.984	0.9919	0.9880	124	0.9333	0.9497	0.9415	0.9868
0.0439	71.0	6816	0.0389	0.9153	0.9310	0.9231	116	0.9074	0.9304	0.9187	158	0.984	0.9919	0.9880	124	0.9333	0.9497	0.9415	0.9871
0.0426	72.0	6912	0.0383	0.9153	0.9310	0.9231	116	0.9006	0.9177	0.9091	158	0.984	0.9919	0.9880	124	0.9307	0.9447	0.9377	0.9860
0.0423	73.0	7008	0.0387	0.9153	0.9310	0.9231	116	0.9074	0.9304	0.9187	158	0.984	0.9919	0.9880	124	0.9333	0.9497	0.9415	0.9871
0.0427	74.0	7104	0.0385	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9871
0.044	75.0	7200	0.0387	0.9153	0.9310	0.9231	116	0.9018	0.9304	0.9159	158	0.984	0.9919	0.9880	124	0.9310	0.9497	0.9403	0.9871
0.0415	76.0	7296	0.0386	0.9153	0.9310	0.9231	116	0.9018	0.9304	0.9159	158	0.984	0.9919	0.9880	124	0.9310	0.9497	0.9403	0.9874
0.0421	77.0	7392	0.0385	0.9153	0.9310	0.9231	116	0.9068	0.9241	0.9154	158	0.984	0.9919	0.9880	124	0.9332	0.9472	0.9401	0.9874
0.0428	78.0	7488	0.0380	0.9153	0.9310	0.9231	116	0.9125	0.9241	0.9182	158	0.984	0.9919	0.9880	124	0.9355	0.9472	0.9413	0.9871
0.0414	79.0	7584	0.0385	0.9153	0.9310	0.9231	116	0.8896	0.9177	0.9034	158	0.984	0.9919	0.9880	124	0.9261	0.9447	0.9353	0.9865
0.0394	80.0	7680	0.0380	0.9153	0.9310	0.9231	116	0.8841	0.9177	0.9006	158	0.984	0.9919	0.9880	124	0.9238	0.9447	0.9342	0.9868
0.0402	81.0	7776	0.0385	0.9153	0.9310	0.9231	116	0.8963	0.9304	0.9130	158	0.984	0.9919	0.9880	124	0.9287	0.9497	0.9391	0.9876
0.0404	82.0	7872	0.0377	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9874
0.0407	83.0	7968	0.0381	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0406	84.0	8064	0.0380	0.9153	0.9310	0.9231	116	0.8902	0.9241	0.9068	158	0.984	0.9919	0.9880	124	0.9263	0.9472	0.9366	0.9874
0.0425	85.0	8160	0.0381	0.9153	0.9310	0.9231	116	0.8963	0.9304	0.9130	158	0.984	0.9919	0.9880	124	0.9287	0.9497	0.9391	0.9876
0.0402	86.0	8256	0.0374	0.9153	0.9310	0.9231	116	0.9062	0.9177	0.9119	158	0.984	0.9919	0.9880	124	0.9330	0.9447	0.9388	0.9868
0.0402	87.0	8352	0.0379	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9871
0.0407	88.0	8448	0.0380	0.9153	0.9310	0.9231	116	0.8902	0.9241	0.9068	158	0.984	0.9919	0.9880	124	0.9263	0.9472	0.9366	0.9874
0.0385	89.0	8544	0.0379	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0388	90.0	8640	0.0377	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0406	91.0	8736	0.0380	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0404	92.0	8832	0.0377	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0409	93.0	8928	0.0377	0.9153	0.9310	0.9231	116	0.8951	0.9177	0.9062	158	0.984	0.9919	0.9880	124	0.9284	0.9447	0.9365	0.9865
0.0382	94.0	9024	0.0380	0.9153	0.9310	0.9231	116	0.8957	0.9241	0.9097	158	0.984	0.9919	0.9880	124	0.9286	0.9472	0.9378	0.9871
0.0409	95.0	9120	0.0379	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9868
0.0406	96.0	9216	0.0379	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9868
0.0413	97.0	9312	0.0378	0.9153	0.9310	0.9231	116	0.8951	0.9177	0.9062	158	0.984	0.9919	0.9880	124	0.9284	0.9447	0.9365	0.9865
0.0384	98.0	9408	0.0379	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9868
0.0394	99.0	9504	0.0379	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9868
0.0386	100.0	9600	0.0379	0.9153	0.9310	0.9231	116	0.9012	0.9241	0.9125	158	0.984	0.9919	0.9880	124	0.9309	0.9472	0.9390	0.9868

Framework versions

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