Melanoma-Classification

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

Model description

More information needed

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More information needed

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9779	0.08	100	1.1158	0.6041
0.9934	0.16	200	1.0227	0.6501
0.9562	0.24	300	0.9276	0.6748
1.0995	0.32	400	0.9088	0.6836
0.8198	0.39	500	0.8581	0.6949
0.8034	0.47	600	0.8444	0.6967
0.8319	0.55	700	0.8196	0.7148
0.787	0.63	800	0.8360	0.6975
0.8642	0.71	900	0.8250	0.7008
0.8329	0.79	1000	0.7939	0.7172
0.9678	0.87	1100	0.7661	0.7332
0.8226	0.95	1200	0.7284	0.7373
0.7967	1.03	1300	0.7355	0.7411
0.6531	1.1	1400	0.7561	0.7247
0.5719	1.18	1500	0.6839	0.7638
0.6123	1.26	1600	0.6857	0.7584
0.6504	1.34	1700	0.6970	0.7531
0.6214	1.42	1800	0.6841	0.7576
0.4925	1.5	1900	0.6624	0.7642
0.5797	1.58	2000	0.6287	0.7709
0.6018	1.66	2100	0.6537	0.7622
0.6334	1.74	2200	0.6413	0.7713
0.4111	1.82	2300	0.6242	0.7786
0.4779	1.89	2400	0.6260	0.7790
0.5488	1.97	2500	0.6146	0.7807
0.3212	2.05	2600	0.6975	0.7707
0.4282	2.13	2700	0.6344	0.7790
0.2822	2.21	2800	0.6985	0.7845
0.3003	2.29	2900	0.5954	0.7993
0.2982	2.37	3000	0.6156	0.7940
0.2628	2.45	3100	0.6318	0.7963
0.2987	2.53	3200	0.6495	0.8030
0.2714	2.6	3300	0.6018	0.8052
0.3059	2.68	3400	0.5944	0.8078
0.2762	2.76	3500	0.6296	0.7936
0.3685	2.84	3600	0.6277	0.8017
0.2299	2.92	3700	0.5834	0.8125
0.3414	3.0	3800	0.5750	0.8167
0.1082	3.08	3900	0.6201	0.8196
0.049	3.16	4000	0.6475	0.8161
0.102	3.24	4100	0.6791	0.8097
0.0483	3.31	4200	0.6582	0.8216
0.1204	3.39	4300	0.6603	0.8222
0.0611	3.47	4400	0.7174	0.8190
0.0555	3.55	4500	0.6841	0.8236
0.0188	3.63	4600	0.7009	0.8240
0.1292	3.71	4700	0.7040	0.8204
0.0661	3.79	4800	0.7074	0.8238
0.1061	3.87	4900	0.6984	0.8210
0.0861	3.95	5000	0.6913	0.8230