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egujr001/
egujr001-swim2-base-model

Name: egujr001-swim2-base-model
Availability: InStock

generated_from_trainer

microsoft/swinv2-tiny-patch4-window8-256

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egujr001-swim2-base-model

This model is a fine-tuned version of microsoft/swinv2-tiny-patch4-window8-256 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1969
Accuracy: 0.9457

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: 64
eval_batch_size: 64
seed: 56
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6254	0.04	100	0.5840	0.7050
0.3998	0.08	200	0.3525	0.8507
0.2796	0.12	300	0.2710	0.8975
0.23	0.15	400	0.2660	0.9012
0.2372	0.19	500	0.1678	0.9401
0.1944	0.23	600	0.1437	0.9437
0.1635	0.27	700	0.1231	0.9503
0.1463	0.31	800	0.1353	0.9551
0.1287	0.35	900	0.1216	0.9523
0.1208	0.39	1000	0.1695	0.9351
0.1204	0.42	1100	0.1221	0.9557
0.1064	0.46	1200	0.1605	0.9432
0.1114	0.5	1300	0.0998	0.9613
0.1324	0.54	1400	0.0888	0.9650
0.0997	0.58	1500	0.0810	0.9686
0.0904	0.62	1600	0.0945	0.9655
0.0975	0.66	1700	0.0978	0.9635
0.0859	0.69	1800	0.0858	0.9696
0.0785	0.73	1900	0.0749	0.9722
0.0743	0.77	2000	0.0763	0.9727
0.0815	0.81	2100	0.0765	0.9728
0.0674	0.85	2200	0.0881	0.9703
0.0726	0.89	2300	0.0875	0.9716
0.0633	0.93	2400	0.0912	0.9721
0.0501	0.96	2500	0.0743	0.9750
0.0927	1.0	2600	0.0695	0.9759
0.0766	1.04	2700	0.0788	0.9733
0.0934	1.08	2800	0.0699	0.9753
0.0714	1.12	2900	0.0756	0.9762
0.069	1.16	3000	0.0859	0.9706
0.0702	1.2	3100	0.1001	0.9658
0.0633	1.23	3200	0.0724	0.9756
0.0756	1.27	3300	0.0734	0.9745
0.0617	1.31	3400	0.0704	0.9747
0.0498	1.35	3500	0.0651	0.9788
0.0668	1.39	3600	0.0625	0.9791
0.0441	1.43	3700	0.0714	0.9774
0.0789	1.46	3800	0.0880	0.9722
0.0464	1.5	3900	0.0720	0.9749
0.0532	1.54	4000	0.0681	0.9782
0.0677	1.58	4100	0.0733	0.9736
0.0654	1.62	4200	0.0610	0.9802
0.0554	1.66	4300	0.0825	0.9740
0.0836	1.7	4400	0.0694	0.9780
0.0688	1.73	4500	0.0599	0.9813
0.052	1.77	4600	0.0932	0.9673
0.0515	1.81	4700	0.0785	0.9759
0.0586	1.85	4800	0.0660	0.9787
0.056	1.89	4900	0.0612	0.9783
0.037	1.93	5000	0.0645	0.9795
0.0541	1.97	5100	0.0600	0.9809
0.0521	2.0	5200	0.0876	0.9737
0.0352	2.04	5300	0.0709	0.9780
0.0498	2.08	5400	0.0610	0.9809
0.0424	2.12	5500	0.0569	0.9830
0.0532	2.16	5600	0.0625	0.9820
0.046	2.2	5700	0.0512	0.9842
0.0453	2.24	5800	0.0608	0.9813
0.0577	2.27	5900	0.0697	0.9811
0.0397	2.31	6000	0.0688	0.9816
0.0494	2.35	6100	0.0534	0.9834
0.0158	2.39	6200	0.0860	0.9774
0.0297	2.43	6300	0.0593	0.9836
0.055	2.47	6400	0.0579	0.9821
0.0368	2.51	6500	0.0729	0.9796
0.0754	2.54	6600	0.0601	0.9827
0.0523	2.58	6700	0.0597	0.9824
0.0433	2.62	6800	0.0547	0.9841
0.0164	2.66	6900	0.0620	0.9827
0.015	2.7	7000	0.0639	0.9822
0.0415	2.74	7100	0.0576	0.9837
0.0257	2.78	7200	0.0620	0.9820
0.0268	2.81	7300	0.0568	0.9837
0.043	2.85	7400	0.0558	0.9836
0.0339	2.89	7500	0.0554	0.9839
0.0263	2.93	7600	0.0552	0.9837
0.0428	2.97	7700	0.0535	0.9842

Framework versions

Transformers 4.33.0
Pytorch 2.0.0+cu117
Datasets 2.19.1
Tokenizers 0.13.3

egujr001/egujr001-swim2-base-model

egujr001-swim2-base-model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

egujr001/
egujr001-swim2-base-model