This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2171
Accuracy: 0.9333
F1: 0.9334
Precision: 0.9384
Recall: 0.9333

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: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
2.1325	0.1136	100	2.0321	0.1833	0.1024	0.0943	0.1833
1.8745	0.2273	200	2.0416	0.1667	0.0541	0.0382	0.1667
2.1848	0.3409	300	2.0512	0.1767	0.0830	0.0671	0.1767
2.2135	0.4545	400	2.0171	0.1667	0.0476	0.0278	0.1667
2.0455	0.5682	500	2.0368	0.2533	0.1505	0.1190	0.2533
2.178	0.6818	600	1.9420	0.2667	0.1447	0.1094	0.2667
2.0375	0.7955	700	1.9715	0.2067	0.1288	0.1051	0.2067
2.1917	0.9091	800	1.9342	0.2733	0.1684	0.1276	0.2733
1.7963	1.0227	900	1.8921	0.2267	0.1141	0.0763	0.2267
2.0072	1.1364	1000	1.9752	0.19	0.1125	0.0960	0.19
1.9791	1.25	1100	1.8841	0.2667	0.1682	0.1684	0.2667
2.1029	1.3636	1200	2.0206	0.2367	0.1075	0.0795	0.2367
2.1388	1.4773	1300	1.8935	0.2767	0.1514	0.1132	0.2767
2.0979	1.5909	1400	1.9137	0.2033	0.1131	0.1240	0.2033
2.3026	1.7045	1500	1.9526	0.27	0.1616	0.1235	0.27
1.5513	1.8182	1600	1.8520	0.2867	0.1743	0.1475	0.2867
2.3849	1.9318	1700	1.8976	0.21	0.1004	0.0768	0.21
1.8575	2.0455	1800	1.9197	0.21	0.1011	0.0782	0.21
1.8156	2.1591	1900	1.8727	0.2767	0.1670	0.1279	0.2767
1.7686	2.2727	2000	1.8727	0.3067	0.2090	0.1648	0.3067
1.6668	2.3864	2100	1.9466	0.24	0.1717	0.1441	0.24
2.0095	2.5	2200	1.9201	0.22	0.1281	0.0992	0.22
2.014	2.6136	2300	1.8951	0.2833	0.1770	0.1412	0.2833
2.1405	2.7273	2400	1.8732	0.29	0.1872	0.1483	0.29
1.4917	2.8409	2500	1.8817	0.2867	0.2120	0.1767	0.2867
2.2975	2.9545	2600	1.8635	0.2567	0.1860	0.1573	0.2567
1.5702	3.0682	2700	1.7966	0.3133	0.2017	0.1621	0.3133
1.9689	3.1818	2800	1.9080	0.2667	0.1841	0.1477	0.2667
1.947	3.2955	2900	1.8981	0.32	0.2062	0.1680	0.32
1.4395	3.4091	3000	1.7913	0.31	0.2131	0.1663	0.31
1.759	3.5227	3100	1.8260	0.2567	0.1808	0.1521	0.2567
1.9838	3.6364	3200	2.0104	0.2733	0.1828	0.1779	0.2733
2.3316	3.75	3300	1.8896	0.2833	0.2262	0.2220	0.2833
2.1299	3.8636	3400	1.8655	0.26	0.2294	0.2674	0.26
1.7605	3.9773	3500	1.7924	0.3133	0.2262	0.2218	0.3133
1.2404	4.0909	3600	1.7928	0.3067	0.2075	0.1666	0.3067
2.1577	4.2045	3700	1.7855	0.31	0.2178	0.1988	0.31
2.3638	4.3182	3800	1.6657	0.36	0.2616	0.2561	0.36
1.5629	4.4318	3900	1.7126	0.3467	0.2556	0.2339	0.3467
1.3863	4.5455	4000	1.7081	0.3533	0.2577	0.2127	0.3533
1.7062	4.6591	4100	1.7079	0.3433	0.3172	0.3025	0.3433
1.8169	4.7727	4200	1.7166	0.3233	0.2824	0.2959	0.3233
1.7194	4.8864	4300	1.6868	0.3367	0.2875	0.2966	0.3367
1.3832	5.0	4400	1.7165	0.35	0.2718	0.2567	0.35
2.5918	5.1136	4500	1.7122	0.3433	0.2933	0.2838	0.3433
1.5676	5.2273	4600	1.7024	0.3333	0.2896	0.3166	0.3333
2.1208	5.3409	4700	1.7090	0.3367	0.2856	0.3237	0.3367
1.8254	5.4545	4800	1.6732	0.39	0.3092	0.2774	0.39
1.6147	5.5682	4900	1.6215	0.3633	0.3220	0.3153	0.3633
0.972	5.6818	5000	1.7132	0.3667	0.2810	0.2491	0.3667
1.617	5.7955	5100	1.7317	0.3833	0.3096	0.2754	0.3833
1.5304	5.9091	5200	1.8030	0.3233	0.2622	0.2641	0.3233
1.5496	6.0227	5300	1.6435	0.3633	0.3171	0.3313	0.3633
1.2992	6.1364	5400	1.7029	0.3533	0.2990	0.2643	0.3533
1.4571	6.25	5500	1.7118	0.3933	0.3344	0.3007	0.3933
1.2905	6.3636	5600	1.5744	0.41	0.3646	0.3419	0.41
2.5343	6.4773	5700	1.6429	0.3867	0.3351	0.3487	0.3867
2.0219	6.5909	5800	1.7131	0.38	0.3056	0.2979	0.38
1.7597	6.7045	5900	1.6401	0.4033	0.3406	0.3349	0.4033
1.4103	6.8182	6000	1.6261	0.41	0.3560	0.4100	0.41
2.2024	6.9318	6100	1.7209	0.37	0.3233	0.3519	0.37
1.2347	7.0455	6200	1.5996	0.39	0.3559	0.3491	0.39
1.2568	7.1591	6300	1.5115	0.4	0.3341	0.3365	0.4
1.7057	7.2727	6400	1.5506	0.42	0.3743	0.3457	0.42
1.4601	7.3864	6500	1.4624	0.44	0.3986	0.3785	0.44
1.8181	7.5	6600	1.4508	0.4533	0.3842	0.3917	0.4533
1.5281	7.6136	6700	1.6279	0.44	0.3812	0.3438	0.44
2.1477	7.7273	6800	1.6037	0.42	0.3809	0.3940	0.42
1.6771	7.8409	6900	1.7062	0.4	0.3404	0.3308	0.4
1.6814	7.9545	7000	1.6030	0.3933	0.3495	0.3876	0.3933
1.7722	8.0682	7100	1.5115	0.4333	0.4010	0.4336	0.4333
1.027	8.1818	7200	1.6255	0.41	0.3556	0.3784	0.41
1.6206	8.2955	7300	1.8537	0.41	0.3379	0.3504	0.41
1.7434	8.4091	7400	1.5531	0.4267	0.3882	0.4349	0.4267
2.1487	8.5227	7500	1.4898	0.4367	0.3854	0.4242	0.4367
1.6752	8.6364	7600	1.6730	0.4133	0.3432	0.3759	0.4133
2.0036	8.75	7700	1.6937	0.3933	0.3543	0.3492	0.3933
2.0274	8.8636	7800	1.6572	0.42	0.3877	0.3727	0.42
1.2597	8.9773	7900	1.5253	0.4633	0.4251	0.5100	0.4633
1.1452	9.0909	8000	1.4956	0.4567	0.4039	0.3766	0.4567
1.398	9.2045	8100	1.6662	0.3633	0.3315	0.4616	0.3633
1.3116	9.3182	8200	1.7941	0.42	0.3844	0.3662	0.42
1.1882	9.4318	8300	1.7093	0.4967	0.4518	0.5084	0.4967
1.7041	9.5455	8400	1.4589	0.5033	0.4848	0.4948	0.5033
1.3751	9.6591	8500	1.5243	0.49	0.4396	0.4786	0.49
2.351	9.7727	8600	1.3950	0.49	0.4787	0.4788	0.49
1.5726	9.8864	8700	1.7219	0.46	0.4054	0.3889	0.46
1.8469	10.0	8800	1.4327	0.4467	0.4139	0.4410	0.4467
1.672	10.1136	8900	1.5570	0.4633	0.4271	0.4525	0.4633
1.4056	10.2273	9000	1.4028	0.48	0.4504	0.5025	0.48
1.0054	10.3409	9100	1.5788	0.4767	0.4473	0.5325	0.4767
1.6323	10.4545	9200	1.3638	0.51	0.5005	0.5339	0.51
2.2599	10.5682	9300	1.9310	0.4467	0.3990	0.4616	0.4467
1.0275	10.6818	9400	1.4148	0.5133	0.4983	0.5204	0.5133
1.5798	10.7955	9500	1.4635	0.49	0.4499	0.4870	0.49
1.2391	10.9091	9600	1.3368	0.53	0.5224	0.5328	0.53
1.4914	11.0227	9700	1.4432	0.5033	0.4696	0.5119	0.5033
0.5783	11.1364	9800	1.7681	0.4567	0.4195	0.4937	0.4567
1.6834	11.25	9900	1.5489	0.4933	0.4432	0.5159	0.4933
1.0594	11.3636	10000	1.4299	0.54	0.5331	0.5552	0.54
1.923	11.4773	10100	1.5363	0.52	0.5089	0.5122	0.52
0.9397	11.5909	10200	1.4348	0.5433	0.5046	0.5540	0.5433
1.3073	11.7045	10300	1.5407	0.5033	0.4829	0.5160	0.5033
1.6012	11.8182	10400	1.5216	0.5033	0.4703	0.5615	0.5033
1.439	11.9318	10500	1.4947	0.5133	0.4914	0.5764	0.5133
1.3553	12.0455	10600	1.3487	0.55	0.5370	0.5715	0.55
1.1319	12.1591	10700	1.4175	0.5433	0.5167	0.5064	0.5433
1.6714	12.2727	10800	1.4944	0.51	0.4915	0.5337	0.51
0.8275	12.3864	10900	1.3419	0.5533	0.5447	0.5615	0.5533
1.4667	12.5	11000	1.4655	0.55	0.5147	0.5655	0.55
1.4694	12.6136	11100	1.3455	0.5433	0.5133	0.5032	0.5433
1.3876	12.7273	11200	1.3658	0.57	0.5424	0.6040	0.57
1.4705	12.8409	11300	1.3043	0.57	0.5533	0.5843	0.57
2.4678	12.9545	11400	1.2052	0.58	0.5660	0.6041	0.58
1.6037	13.0682	11500	1.3322	0.54	0.5304	0.5558	0.54
0.8944	13.1818	11600	1.3380	0.57	0.5373	0.6221	0.57
1.2658	13.2955	11700	1.5095	0.5267	0.5038	0.5470	0.5267
2.0735	13.4091	11800	1.2082	0.6167	0.6047	0.6207	0.6167
1.0294	13.5227	11900	1.1833	0.5967	0.5891	0.6527	0.5967
0.8701	13.6364	12000	1.3908	0.5767	0.5572	0.6046	0.5767
1.8376	13.75	12100	1.2818	0.59	0.5833	0.6043	0.59
1.1665	13.8636	12200	1.1787	0.61	0.6032	0.6067	0.61
1.578	13.9773	12300	1.4198	0.5533	0.5540	0.5973	0.5533
0.7219	14.0909	12400	1.4571	0.5733	0.5588	0.5684	0.5733
0.9484	14.2045	12500	1.3443	0.5733	0.5676	0.5980	0.5733
1.1644	14.3182	12600	1.1967	0.64	0.6254	0.6571	0.64
1.6737	14.4318	12700	1.1579	0.6133	0.6114	0.6493	0.6133
0.4206	14.5455	12800	1.1327	0.65	0.6485	0.6636	0.65
1.7619	14.6591	12900	1.2594	0.6	0.5982	0.6673	0.6
1.4951	14.7727	13000	1.1301	0.65	0.6293	0.6649	0.65
2.0405	14.8864	13100	1.1906	0.63	0.6192	0.6357	0.63
1.5169	15.0	13200	1.1900	0.6333	0.6238	0.6446	0.6333
1.517	15.1136	13300	1.1868	0.6367	0.6269	0.6431	0.6367
1.8484	15.2273	13400	1.2448	0.6433	0.6236	0.6798	0.6433
1.3278	15.3409	13500	1.0725	0.66	0.6574	0.6810	0.66
1.2777	15.4545	13600	1.1123	0.65	0.6500	0.6620	0.65
1.5833	15.5682	13700	1.1579	0.6533	0.6505	0.6630	0.6533
1.2333	15.6818	13800	1.0351	0.67	0.6679	0.7362	0.67
1.9318	15.7955	13900	1.0084	0.6833	0.6821	0.6972	0.6833
1.2167	15.9091	14000	1.0112	0.67	0.6688	0.6893	0.67
1.3955	16.0227	14100	1.1367	0.65	0.6424	0.6675	0.65
1.6943	16.1364	14200	1.1927	0.6567	0.6581	0.6878	0.6567
2.3253	16.25	14300	1.1678	0.68	0.6712	0.6906	0.68
1.3754	16.3636	14400	1.0888	0.6667	0.6646	0.6757	0.6667
0.9967	16.4773	14500	1.1972	0.5967	0.5899	0.6351	0.5967
1.1325	16.5909	14600	1.1720	0.66	0.6581	0.6725	0.66
1.2693	16.7045	14700	1.0738	0.67	0.6609	0.6775	0.67
2.177	16.8182	14800	1.2318	0.6267	0.6097	0.6219	0.6267
1.9631	16.9318	14900	1.0616	0.7033	0.6951	0.7380	0.7033
0.4307	17.0455	15000	1.1593	0.6767	0.6751	0.7137	0.6767
1.5144	17.1591	15100	1.1575	0.6867	0.6816	0.7203	0.6867
1.0533	17.2727	15200	0.9916	0.7233	0.7147	0.7443	0.7233
2.0933	17.3864	15300	1.1640	0.69	0.6817	0.7049	0.69
0.7733	17.5	15400	1.0627	0.7033	0.6961	0.7222	0.7033
1.942	17.6136	15500	1.0537	0.72	0.7157	0.7453	0.72
0.1422	17.7273	15600	1.0434	0.6867	0.6773	0.6873	0.6867
1.6104	17.8409	15700	0.9983	0.7167	0.7183	0.7457	0.7167
2.0064	17.9545	15800	1.0145	0.71	0.7031	0.7177	0.71
1.5486	18.0682	15900	1.1365	0.7033	0.6973	0.7088	0.7033
2.7864	18.1818	16000	1.0285	0.73	0.7263	0.7446	0.73
1.213	18.2955	16100	1.0124	0.72	0.7119	0.7229	0.72
1.5922	18.4091	16200	1.1702	0.6633	0.6473	0.6508	0.6633
0.575	18.5227	16300	0.9927	0.74	0.7354	0.7483	0.74
1.2907	18.6364	16400	0.9610	0.7467	0.7471	0.7677	0.7467
1.2497	18.75	16500	0.9740	0.7267	0.7299	0.7562	0.7267
0.9504	18.8636	16600	0.8175	0.7667	0.7678	0.7851	0.7667
2.0678	18.9773	16700	1.0185	0.7267	0.7306	0.7610	0.7267
1.5767	19.0909	16800	1.3069	0.7	0.6941	0.7026	0.7
1.0399	19.2045	16900	1.0427	0.7133	0.7075	0.7134	0.7133
1.1016	19.3182	17000	0.7514	0.78	0.7781	0.7834	0.78
1.3244	19.4318	17100	0.8616	0.7833	0.7824	0.7945	0.7833
1.0574	19.5455	17200	1.0000	0.7533	0.7541	0.7798	0.7533
1.3972	19.6591	17300	1.0219	0.74	0.7370	0.7604	0.74
0.549	19.7727	17400	0.8382	0.7733	0.7701	0.7929	0.7733
1.2579	19.8864	17500	0.9918	0.7367	0.7361	0.7571	0.7367
2.4236	20.0	17600	1.2059	0.6733	0.6612	0.7173	0.6733
0.7265	20.1136	17700	0.8236	0.78	0.7758	0.7820	0.78
1.948	20.2273	17800	0.9320	0.77	0.7682	0.7870	0.77
2.0043	20.3409	17900	0.7740	0.7867	0.7849	0.7985	0.7867
1.0796	20.4545	18000	0.8225	0.78	0.7785	0.8069	0.78
1.4089	20.5682	18100	0.8105	0.78	0.7758	0.7872	0.78
0.3034	20.6818	18200	0.7958	0.78	0.7741	0.7793	0.78
0.8838	20.7955	18300	0.8089	0.8133	0.8099	0.8220	0.8133
1.4591	20.9091	18400	0.7593	0.8033	0.7995	0.8114	0.8033
1.1545	21.0227	18500	1.1446	0.7233	0.7253	0.7499	0.7233
0.732	21.1364	18600	0.7913	0.7967	0.7946	0.8040	0.7967
0.3987	21.25	18700	0.8410	0.7867	0.7819	0.7974	0.7867
1.0486	21.3636	18800	0.8319	0.7833	0.7776	0.7997	0.7833
0.5063	21.4773	18900	0.8443	0.8067	0.8020	0.8178	0.8067
0.7905	21.5909	19000	0.9596	0.77	0.7612	0.7790	0.77
0.7717	21.7045	19100	0.9244	0.8033	0.8005	0.8166	0.8033
0.5365	21.8182	19200	0.9661	0.7633	0.7597	0.7778	0.7633
0.8991	21.9318	19300	0.7786	0.7867	0.7820	0.7958	0.7867
0.6671	22.0455	19400	0.6612	0.8233	0.8200	0.8351	0.8233
0.4713	22.1591	19500	0.7054	0.8267	0.8217	0.8353	0.8267
0.7041	22.2727	19600	0.7471	0.8	0.7952	0.8153	0.8
0.197	22.3864	19700	0.6874	0.8267	0.8241	0.8396	0.8267
0.353	22.5	19800	0.7304	0.82	0.8161	0.8272	0.82
1.184	22.6136	19900	0.7151	0.82	0.8150	0.8290	0.82
1.3648	22.7273	20000	0.7410	0.8167	0.8132	0.8209	0.8167
0.9501	22.8409	20100	0.6499	0.8167	0.8159	0.8266	0.8167
0.262	22.9545	20200	0.6300	0.8367	0.8317	0.8459	0.8367
0.2318	23.0682	20300	0.8589	0.79	0.7858	0.7934	0.79
0.8504	23.1818	20400	0.6944	0.83	0.8272	0.8364	0.83
0.3976	23.2955	20500	0.6853	0.83	0.8253	0.8380	0.83
0.0863	23.4091	20600	0.7087	0.83	0.8268	0.8424	0.83
0.1308	23.5227	20700	0.6115	0.84	0.8377	0.8454	0.84
0.5146	23.6364	20800	0.6218	0.84	0.8361	0.8416	0.84
0.8203	23.75	20900	0.5224	0.8567	0.8552	0.8588	0.8567
1.1872	23.8636	21000	0.5631	0.85	0.8470	0.8569	0.85
1.0908	23.9773	21100	0.5524	0.85	0.8462	0.8585	0.85
0.0022	24.0909	21200	0.5363	0.86	0.8578	0.8673	0.86
1.6888	24.2045	21300	0.6602	0.8367	0.8304	0.8421	0.8367
0.2682	24.3182	21400	0.5271	0.86	0.8585	0.8680	0.86
0.2807	24.4318	21500	0.4464	0.8733	0.8716	0.8787	0.8733
0.2431	24.5455	21600	0.5111	0.8567	0.8535	0.8594	0.8567
2.7275	24.6591	21700	0.4631	0.8767	0.8750	0.8825	0.8767
0.706	24.7727	21800	0.5497	0.8533	0.8530	0.8580	0.8533
0.3191	24.8864	21900	0.6010	0.85	0.8499	0.8602	0.85
1.0717	25.0	22000	0.4868	0.8767	0.8759	0.8860	0.8767
1.0237	25.1136	22100	0.4212	0.87	0.8700	0.8766	0.87
0.3669	25.2273	22200	0.4204	0.88	0.8780	0.8851	0.88
0.2923	25.3409	22300	0.5041	0.8733	0.8726	0.8834	0.8733
0.468	25.4545	22400	0.5242	0.8633	0.8638	0.8707	0.8633
0.0333	25.5682	22500	0.3914	0.8967	0.8961	0.9014	0.8967
0.7682	25.6818	22600	0.4016	0.8867	0.8858	0.8912	0.8867
0.1863	25.7955	22700	0.4485	0.8833	0.8826	0.8927	0.8833
1.1239	25.9091	22800	0.4287	0.89	0.8896	0.8994	0.89
0.6257	26.0227	22900	0.3714	0.8933	0.8924	0.9008	0.8933
0.2438	26.1364	23000	0.4003	0.8933	0.8927	0.9002	0.8933
0.0027	26.25	23100	0.3834	0.9	0.9002	0.9059	0.9
0.5624	26.3636	23200	0.3970	0.9	0.9004	0.9089	0.9
0.0127	26.4773	23300	0.3772	0.8967	0.8955	0.8996	0.8967
0.7248	26.5909	23400	0.3919	0.8933	0.8915	0.8977	0.8933
0.7947	26.7045	23500	0.3874	0.9033	0.9019	0.9053	0.9033
0.7292	26.8182	23600	0.3422	0.91	0.9091	0.9139	0.91
0.047	26.9318	23700	0.2923	0.9167	0.9166	0.9219	0.9167
0.5063	27.0455	23800	0.3153	0.9133	0.9130	0.9188	0.9133
0.4127	27.1591	23900	0.3273	0.9133	0.9129	0.9175	0.9133
0.0093	27.2727	24000	0.3658	0.9133	0.9127	0.9179	0.9133
0.4859	27.3864	24100	0.3952	0.9033	0.9029	0.9061	0.9033
0.0075	27.5	24200	0.3231	0.9133	0.9132	0.9181	0.9133
0.0021	27.6136	24300	0.3003	0.91	0.9097	0.9127	0.91
1.1539	27.7273	24400	0.3282	0.9167	0.9164	0.9187	0.9167
0.4621	27.8409	24500	0.2971	0.9167	0.9168	0.9222	0.9167
0.6388	27.9545	24600	0.2677	0.9233	0.9241	0.9292	0.9233
0.4187	28.0682	24700	0.2462	0.92	0.9206	0.9255	0.92
0.3007	28.1818	24800	0.2599	0.9233	0.9241	0.9302	0.9233
0.0099	28.2955	24900	0.2981	0.9133	0.9125	0.9177	0.9133
1.1637	28.4091	25000	0.2819	0.9167	0.9167	0.9219	0.9167
0.0701	28.5227	25100	0.2788	0.92	0.9205	0.9267	0.92
0.6484	28.6364	25200	0.2541	0.9267	0.9268	0.9346	0.9267
0.0016	28.75	25300	0.2422	0.9333	0.9335	0.9389	0.9333
1.2359	28.8636	25400	0.2319	0.93	0.9300	0.9355	0.93
0.3842	28.9773	25500	0.2229	0.9333	0.9337	0.9384	0.9333
0.751	29.0909	25600	0.2323	0.9267	0.9274	0.9338	0.9267
0.4643	29.2045	25700	0.2354	0.9333	0.9338	0.9400	0.9333
0.8059	29.3182	25800	0.2268	0.9333	0.9336	0.9391	0.9333
0.2155	29.4318	25900	0.2322	0.9333	0.9336	0.9391	0.9333
0.628	29.5455	26000	0.2306	0.9333	0.9336	0.9391	0.9333
0.1146	29.6591	26100	0.2243	0.9333	0.9334	0.9384	0.9333
0.2068	29.7727	26200	0.2155	0.9333	0.9334	0.9384	0.9333
0.0016	29.8864	26300	0.2176	0.9333	0.9334	0.9384	0.9333
0.002	30.0	26400	0.2171	0.9333	0.9334	0.9384	0.9333

Framework versions

Transformers 4.52.4
Pytorch 2.7.0
Datasets 3.6.0
Tokenizers 0.21.1

Larbz-7/test

radioup-model-v5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Larbz-7/
test