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Ayushij074/
swinv2-tiny-patch4-window8-256-finetuned-eurosat

Name: swinv2-tiny-patch4-window8-256-finetuned-eurosat
Availability: InStock

generated_from_trainer

microsoft/swinv2-tiny-patch4-window8-256

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swinv2-tiny-patch4-window8-256-finetuned-eurosat

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0776
Accuracy: 0.9686
Precision Overall: 0.9697
Recall Overall: 0.9686
F1 Overall: 0.9679
Precision T0: 0.9333
Recall T0: 0.7368
F1 T0: 0.8235
Precision T1: 0.8893
Recall T1: 0.9765
F1 T1: 0.9308
Precision T2: 0.9939
Recall T2: 0.9889
F1 T2: 0.9914

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: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
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
lr_scheduler_warmup_ratio: 0.1
num_epochs: 100

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Overall	Recall Overall	F1 Overall	Precision T0	Recall T0	F1 T0	Precision T1	Recall T1	F1 T1	Precision T2	Recall T2	F1 T2
1.4522	0.9524	10	1.1098	0.2801	0.7200	0.2801	0.3433	0.1199	0.9053	0.2118	0.0303	0.0392	0.0342	0.9555	0.2821	0.4356
0.9137	1.9286	20	0.6271	0.7386	0.5455	0.7386	0.6276	0.0	0.0	0.0	0.0	0.0	0.0	0.7386	1.0	0.8497
0.6332	2.9048	30	0.5053	0.7498	0.6819	0.7498	0.6553	0.0	0.0	0.0	0.6667	0.0627	0.1147	0.7513	0.9990	0.8576
0.4977	3.9762	41	0.3550	0.8656	0.8133	0.8656	0.8374	0.0	0.0	0.0	0.6511	0.8196	0.7257	0.9332	0.9606	0.9467
0.396	4.9524	51	0.3010	0.8820	0.8191	0.8820	0.8494	0.0	0.0	0.0	0.7279	0.7765	0.7514	0.9213	0.9939	0.9562
0.3438	5.9286	61	0.2886	0.8730	0.8732	0.8730	0.8659	0.4182	0.4842	0.4488	0.8424	0.5451	0.6619	0.9248	0.9949	0.9586
0.3112	6.9048	71	0.2835	0.8574	0.8846	0.8574	0.8492	0.3626	0.6526	0.4662	0.8850	0.3922	0.5435	0.9346	0.9970	0.9648
0.2826	7.9762	82	0.2100	0.9149	0.9115	0.9149	0.9103	0.6437	0.5895	0.6154	0.9005	0.7098	0.7939	0.9401	0.9990	0.9686
0.2627	8.9524	92	0.2164	0.9081	0.9144	0.9081	0.9060	0.5484	0.7158	0.6210	0.9066	0.6471	0.7551	0.9516	0.9939	0.9723
0.2385	9.9286	102	0.2145	0.9089	0.9217	0.9089	0.9065	0.5515	0.7895	0.6494	0.9576	0.6196	0.7524	0.9480	0.9949	0.9709
0.2448	10.9048	112	0.2168	0.9111	0.9216	0.9111	0.9093	0.5746	0.8105	0.6725	0.9425	0.6431	0.7646	0.9496	0.9899	0.9693
0.2353	11.9762	123	0.1721	0.9276	0.9302	0.9276	0.9252	0.6729	0.7579	0.7129	0.9534	0.7216	0.8214	0.9490	0.9970	0.9724
0.2207	12.9524	133	0.1434	0.9447	0.9431	0.9447	0.9418	0.8986	0.6526	0.7561	0.9185	0.8392	0.8770	0.9537	1.0	0.9763
0.1997	13.9286	143	0.1606	0.9283	0.9290	0.9283	0.9264	0.6635	0.7263	0.6935	0.9220	0.7412	0.8217	0.9563	0.9960	0.9757
0.2022	14.9048	153	0.1486	0.9380	0.9392	0.9380	0.9329	0.9796	0.5053	0.6667	0.8544	0.8745	0.8643	0.9572	0.9960	0.9762
0.1899	15.9762	164	0.1402	0.9425	0.9420	0.9425	0.9409	0.7812	0.7895	0.7853	0.9355	0.7961	0.8602	0.9591	0.9949	0.9767
0.1925	16.9524	174	0.1338	0.9432	0.9413	0.9432	0.9410	0.8767	0.6737	0.7619	0.8893	0.8510	0.8697	0.9609	0.9929	0.9766
0.177	17.9286	184	0.1521	0.9395	0.9408	0.9395	0.9351	0.9608	0.5158	0.6712	0.8407	0.8902	0.8648	0.9646	0.9929	0.9786
0.1889	18.9048	194	0.1357	0.9447	0.9442	0.9447	0.9415	0.9508	0.6105	0.7436	0.8871	0.8627	0.8748	0.9583	0.9980	0.9777
0.1972	19.9762	205	0.1303	0.9462	0.9444	0.9462	0.9441	0.8701	0.7053	0.7791	0.9185	0.8392	0.8770	0.9582	0.9970	0.9772
0.1923	20.9524	215	0.1344	0.9403	0.9412	0.9403	0.9389	0.7308	0.8	0.7638	0.9431	0.7804	0.8541	0.9609	0.9949	0.9776
0.1859	21.9286	225	0.1228	0.9455	0.9431	0.9455	0.9434	0.8228	0.6842	0.7471	0.9076	0.8471	0.8763	0.9638	0.9960	0.9796
0.1784	22.9048	235	0.1194	0.9470	0.9452	0.9470	0.9448	0.8889	0.6737	0.7665	0.8907	0.8627	0.8765	0.9647	0.9949	0.9796
0.175	23.9762	246	0.1190	0.9432	0.9426	0.9432	0.9421	0.7449	0.7684	0.7565	0.9156	0.8078	0.8583	0.9685	0.9949	0.9815
0.1722	24.9524	256	0.1204	0.9477	0.9461	0.9477	0.9461	0.8068	0.7474	0.7760	0.9254	0.8275	0.8737	0.9648	0.9980	0.9811
0.1727	25.9286	266	0.1168	0.9492	0.9473	0.9492	0.9475	0.8519	0.7263	0.7841	0.9114	0.8471	0.8780	0.9657	0.9970	0.9811
0.1774	26.9048	276	0.1190	0.9507	0.9513	0.9507	0.9497	0.7822	0.8316	0.8061	0.9585	0.8157	0.8814	0.9657	0.9970	0.9811
0.1769	27.9762	287	0.1093	0.9500	0.9484	0.9500	0.9481	0.8904	0.6842	0.7738	0.892	0.8745	0.8832	0.9685	0.9949	0.9815
0.1536	28.9524	297	0.1069	0.9507	0.9496	0.9507	0.9484	0.9275	0.6737	0.7805	0.9024	0.8706	0.8862	0.9639	0.9980	0.9806
0.1625	29.9286	307	0.1022	0.9559	0.9549	0.9559	0.9544	0.9211	0.7368	0.8187	0.9253	0.8745	0.8992	0.9658	0.9980	0.9816
0.1596	30.9048	317	0.1000	0.9552	0.9539	0.9552	0.9542	0.8409	0.7789	0.8087	0.9205	0.8627	0.8907	0.9733	0.9960	0.9845
0.166	31.9762	328	0.1028	0.9537	0.9522	0.9537	0.9526	0.8372	0.7579	0.7956	0.9095	0.8667	0.8876	0.9743	0.9949	0.9845
0.1507	32.9524	338	0.1034	0.9500	0.9498	0.9500	0.9495	0.77	0.8105	0.7897	0.9149	0.8431	0.8776	0.9761	0.9909	0.9834
0.1603	33.9286	348	0.0991	0.9515	0.9499	0.9515	0.9502	0.8554	0.7474	0.7978	0.8980	0.8627	0.8800	0.9723	0.9939	0.9830
0.1431	34.9048	358	0.1069	0.9507	0.9542	0.9507	0.9492	0.9836	0.6316	0.7692	0.8362	0.9412	0.8856	0.9818	0.9838	0.9828
0.1504	35.9762	369	0.1035	0.9544	0.9562	0.9544	0.9522	0.9833	0.6211	0.7613	0.8613	0.9255	0.8922	0.9781	0.9939	0.9860
0.1429	36.9524	379	0.0987	0.9567	0.9574	0.9567	0.9547	0.9531	0.6421	0.7673	0.8713	0.9294	0.8994	0.9801	0.9939	0.9869
0.1471	37.9286	389	0.1180	0.9507	0.9542	0.9507	0.9470	0.9804	0.5263	0.6849	0.8368	0.9451	0.8877	0.982	0.9929	0.9874
0.1421	38.9048	399	0.1058	0.9507	0.9562	0.9507	0.9492	0.9831	0.6105	0.7532	0.82	0.9647	0.8865	0.9888	0.9798	0.9843
0.1342	39.9762	410	0.0953	0.9567	0.9586	0.9567	0.9546	0.9836	0.6316	0.7692	0.8664	0.9412	0.9023	0.9800	0.9919	0.9859
0.1434	40.9524	420	0.0937	0.9612	0.9648	0.9612	0.9596	0.9839	0.6421	0.7771	0.8527	0.9765	0.9104	0.9919	0.9879	0.9899
0.1401	41.9286	430	0.0875	0.9619	0.9609	0.9619	0.9612	0.8523	0.7895	0.8197	0.9268	0.8941	0.9102	0.9801	0.9960	0.9880
0.1342	42.9048	440	0.0875	0.9597	0.9586	0.9597	0.9587	0.8765	0.7474	0.8068	0.9059	0.9059	0.9059	0.9801	0.9939	0.9869
0.1363	43.9762	451	0.1002	0.9597	0.9611	0.9597	0.9574	0.9836	0.6316	0.7692	0.8791	0.9412	0.9091	0.9801	0.9960	0.9880
0.1375	44.9524	461	0.1123	0.9552	0.9560	0.9552	0.9523	0.9831	0.6105	0.7532	0.8893	0.9137	0.9014	0.9705	0.9990	0.9846
0.1373	45.9286	471	0.1053	0.9567	0.9579	0.9567	0.9544	0.9836	0.6316	0.7692	0.8773	0.9255	0.9008	0.9762	0.9960	0.9860
0.135	46.9048	481	0.0947	0.9589	0.9615	0.9589	0.9573	0.9683	0.6421	0.7722	0.8566	0.9608	0.9057	0.9879	0.9889	0.9884
0.1319	47.9762	492	0.0995	0.9567	0.9601	0.9567	0.9548	0.9833	0.6211	0.7613	0.8478	0.9608	0.9007	0.9869	0.9879	0.9874
0.1318	48.9524	502	0.0882	0.9604	0.9604	0.9604	0.9599	0.8875	0.7474	0.8114	0.8810	0.9294	0.9046	0.9879	0.9889	0.9884
0.134	49.9286	512	0.0872	0.9589	0.9587	0.9589	0.9583	0.8765	0.7474	0.8068	0.8797	0.9176	0.8983	0.9869	0.9899	0.9884
0.1233	50.9048	522	0.0858	0.9627	0.9651	0.9627	0.9618	0.9565	0.6947	0.8049	0.8606	0.9686	0.9114	0.9929	0.9869	0.9899
0.1277	51.9762	533	0.0905	0.9612	0.9630	0.9612	0.9605	0.9178	0.7053	0.7976	0.8601	0.9647	0.9094	0.9939	0.9848	0.9893
0.1301	52.9524	543	0.0870	0.9634	0.9645	0.9634	0.9628	0.92	0.7263	0.8118	0.875	0.9608	0.9159	0.9919	0.9869	0.9894
0.1237	53.9286	553	0.0947	0.9619	0.9626	0.9619	0.9605	0.9420	0.6842	0.7927	0.8836	0.9529	0.9170	0.9849	0.9909	0.9879
0.1244	54.9048	563	0.0936	0.9604	0.9611	0.9604	0.9590	0.9559	0.6842	0.7975	0.8856	0.9412	0.9125	0.981	0.9919	0.9864
0.1247	55.9762	574	0.0946	0.9634	0.9648	0.9634	0.9629	0.9211	0.7368	0.8187	0.8723	0.9647	0.9162	0.9929	0.9848	0.9888
0.1179	56.9524	584	0.0930	0.9656	0.9677	0.9656	0.9644	0.9701	0.6842	0.8025	0.8768	0.9765	0.9239	0.9909	0.9899	0.9904
0.1249	57.9286	594	0.0906	0.9634	0.9647	0.9634	0.9623	0.9429	0.6947	0.8000	0.875	0.9608	0.9159	0.9899	0.9899	0.9899
0.1258	58.9048	604	0.0866	0.9627	0.9628	0.9627	0.9621	0.8875	0.7474	0.8114	0.8856	0.9412	0.9125	0.9899	0.9889	0.9894
0.1168	59.9762	615	0.0886	0.9574	0.9586	0.9574	0.9574	0.8452	0.7474	0.7933	0.8602	0.9412	0.8989	0.9949	0.9818	0.9883
0.1267	60.9524	625	0.0951	0.9619	0.9624	0.9619	0.9605	0.9420	0.6842	0.7927	0.8864	0.9490	0.9167	0.9840	0.9919	0.9879
0.1211	61.9286	635	0.0914	0.9612	0.9622	0.9612	0.9597	0.9552	0.6737	0.7901	0.8804	0.9529	0.9153	0.9839	0.9909	0.9874
0.1258	62.9048	645	0.0857	0.9649	0.9659	0.9649	0.9640	0.9444	0.7158	0.8144	0.8845	0.9608	0.9211	0.9889	0.9899	0.9894
0.1165	63.9762	656	0.0831	0.9679	0.9681	0.9679	0.9675	0.9012	0.7684	0.8295	0.8971	0.9569	0.9260	0.9929	0.9899	0.9914
0.1166	64.9524	666	0.0841	0.9634	0.9634	0.9634	0.9634	0.8065	0.7895	0.7979	0.9073	0.9216	0.9144	0.9929	0.9909	0.9919
0.117	65.9286	676	0.0885	0.9627	0.9643	0.9627	0.9615	0.9420	0.6842	0.7927	0.8693	0.9647	0.9145	0.9909	0.9889	0.9899
0.1173	66.9048	686	0.0879	0.9656	0.9657	0.9656	0.9646	0.9452	0.7263	0.8214	0.9064	0.9490	0.9272	0.9830	0.9929	0.9879
0.1133	67.9762	697	0.0850	0.9664	0.9681	0.9664	0.9656	0.9444	0.7158	0.8144	0.8768	0.9765	0.9239	0.9939	0.9879	0.9909
0.1186	68.9524	707	0.0872	0.9642	0.9657	0.9642	0.9634	0.9315	0.7158	0.8095	0.8728	0.9686	0.9182	0.9929	0.9869	0.9899
0.1181	69.9286	717	0.0842	0.9694	0.9704	0.9694	0.9687	0.9333	0.7368	0.8235	0.8893	0.9765	0.9308	0.9949	0.9899	0.9924
0.1062	70.9048	727	0.0856	0.9686	0.9693	0.9686	0.9680	0.9342	0.7474	0.8304	0.8945	0.9647	0.9283	0.9919	0.9909	0.9914
0.1159	71.9762	738	0.0878	0.9656	0.9682	0.9656	0.9648	0.9565	0.6947	0.8049	0.8651	0.9804	0.9191	0.9959	0.9879	0.9919
0.1162	72.9524	748	0.0851	0.9642	0.9644	0.9642	0.9643	0.8021	0.8105	0.8063	0.9141	0.9176	0.9159	0.9929	0.9909	0.9919
0.1201	73.9286	758	0.0828	0.9694	0.9703	0.9694	0.9685	0.9452	0.7263	0.8214	0.8957	0.9765	0.9343	0.9919	0.9909	0.9914
0.1145	74.9048	768	0.0865	0.9656	0.9670	0.9656	0.9642	0.9552	0.6737	0.7901	0.8826	0.9725	0.9254	0.9899	0.9919	0.9909
0.1172	75.9762	779	0.0835	0.9694	0.9693	0.9694	0.9692	0.8539	0.8	0.8261	0.9129	0.9451	0.9287	0.9949	0.9919	0.9934
0.1077	76.9524	789	0.0896	0.9679	0.9695	0.9679	0.9669	0.9571	0.7053	0.8121	0.8834	0.9804	0.9294	0.9929	0.9899	0.9914
0.1093	77.9286	799	0.0808	0.9686	0.9696	0.9686	0.9681	0.9221	0.7474	0.8256	0.8889	0.9725	0.9288	0.9949	0.9889	0.9919
0.1114	78.9048	809	0.0823	0.9642	0.9651	0.9642	0.9639	0.8889	0.7579	0.8182	0.8781	0.9608	0.9176	0.9949	0.9848	0.9898
0.1144	79.9762	820	0.0867	0.9686	0.9705	0.9686	0.9675	0.9706	0.6947	0.8098	0.8838	0.9843	0.9314	0.9929	0.9909	0.9919
0.1101	80.9524	830	0.0786	0.9679	0.9675	0.9679	0.9673	0.8889	0.7579	0.8182	0.9101	0.9529	0.9310	0.9899	0.9919	0.9909
0.1053	81.9286	840	0.0874	0.9679	0.9697	0.9679	0.9669	0.9571	0.7053	0.8121	0.8807	0.9843	0.9296	0.9939	0.9889	0.9914
0.1019	82.9048	850	0.0842	0.9642	0.9660	0.9642	0.9640	0.9114	0.7579	0.8276	0.8702	0.9725	0.9185	0.9959	0.9818	0.9888
0.1086	83.9762	861	0.0864	0.9694	0.9708	0.9694	0.9684	0.9577	0.7158	0.8193	0.8901	0.9843	0.9348	0.9929	0.9899	0.9914
0.1108	84.9524	871	0.0808	0.9634	0.9646	0.9634	0.9630	0.8974	0.7368	0.8092	0.8723	0.9647	0.9162	0.9949	0.9848	0.9898
0.1017	85.9286	881	0.0825	0.9686	0.9704	0.9686	0.9677	0.9577	0.7158	0.8193	0.8838	0.9843	0.9314	0.9939	0.9889	0.9914
0.1108	86.9048	891	0.0800	0.9694	0.9700	0.9694	0.9688	0.9221	0.7474	0.8256	0.8953	0.9725	0.9323	0.9939	0.9899	0.9919
0.1081	87.9762	902	0.0867	0.9679	0.9702	0.9679	0.9669	0.9710	0.7053	0.8171	0.8780	0.9882	0.9299	0.9939	0.9879	0.9909
0.1076	88.9524	912	0.0789	0.9716	0.9720	0.9716	0.9708	0.9333	0.7368	0.8235	0.9055	0.9765	0.9396	0.9929	0.9929	0.9929
0.1059	89.9286	922	0.0829	0.9694	0.9708	0.9694	0.9685	0.9583	0.7263	0.8263	0.8897	0.9804	0.9328	0.9929	0.9899	0.9914
0.1048	90.9048	932	0.0771	0.9716	0.9718	0.9716	0.9709	0.9221	0.7474	0.8256	0.9084	0.9725	0.9394	0.9929	0.9929	0.9929
0.098	91.9762	943	0.0796	0.9709	0.9715	0.9709	0.9701	0.9333	0.7368	0.8235	0.8986	0.9725	0.9341	0.9939	0.9929	0.9934
0.1075	92.9524	953	0.0798	0.9679	0.9689	0.9679	0.9673	0.9211	0.7368	0.8187	0.8857	0.9725	0.9271	0.9949	0.9889	0.9919
0.0937	93.9286	963	0.0777	0.9701	0.9709	0.9701	0.9694	0.9333	0.7368	0.8235	0.8957	0.9765	0.9343	0.9939	0.9909	0.9924
0.1099	94.9048	973	0.0760	0.9679	0.9685	0.9679	0.9673	0.9103	0.7474	0.8208	0.8917	0.9686	0.9286	0.9939	0.9889	0.9914
0.1043	95.9762	984	0.0763	0.9701	0.9710	0.9701	0.9695	0.9342	0.7474	0.8304	0.8957	0.9765	0.9343	0.9939	0.9899	0.9919
0.1013	96.9524	994	0.0774	0.9686	0.9697	0.9686	0.9679	0.9333	0.7368	0.8235	0.8893	0.9765	0.9308	0.9939	0.9889	0.9914
0.1097	97.5476	1000	0.0776	0.9686	0.9697	0.9686	0.9679	0.9333	0.7368	0.8235	0.8893	0.9765	0.9308	0.9939	0.9889	0.9914

Framework versions

Transformers 4.46.3
Pytorch 2.4.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3

Ayushij074/swinv2-tiny-patch4-window8-256-finetuned-eurosat

swinv2-tiny-patch4-window8-256-finetuned-eurosat

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Ayushij074/
swinv2-tiny-patch4-window8-256-finetuned-eurosat