hushem_5x_deit_small_adamax_001_fold2

This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

• Loss: 5.1428
• Accuracy: 0.5556

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: 0.001
• train_batch_size: 32
• eval_batch_size: 32
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.3869	1.0	27	1.3961	0.2444
1.1374	2.0	54	1.4468	0.4222
0.928	3.0	81	1.5182	0.5111
1.0235	4.0	108	1.5182	0.5333
0.797	5.0	135	1.2483	0.3778
0.8238	6.0	162	1.2902	0.5333
0.7166	7.0	189	1.5715	0.4889
0.6354	8.0	216	1.5461	0.4
0.5304	9.0	243	2.1851	0.5111
0.5677	10.0	270	2.3132	0.4222
0.4857	11.0	297	2.4291	0.5556
0.3582	12.0	324	2.5091	0.4444
0.3326	13.0	351	2.6635	0.5556
0.3365	14.0	378	2.7106	0.6
0.3145	15.0	405	3.0588	0.5556
0.1837	16.0	432	3.1156	0.5778
0.277	17.0	459	2.8497	0.5778
0.1371	18.0	486	3.1885	0.6222
0.2815	19.0	513	3.0392	0.5778
0.1153	20.0	540	3.8749	0.5778
0.2394	21.0	567	2.9618	0.5111
0.2767	22.0	594	2.7586	0.5333
0.0906	23.0	621	4.0821	0.5333
0.1246	24.0	648	3.7041	0.4889
0.0582	25.0	675	4.8478	0.5778
0.0262	26.0	702	3.9021	0.5556
0.0436	27.0	729	4.3474	0.5778
0.0484	28.0	756	4.4662	0.5778
0.0031	29.0	783	4.8306	0.5778
0.0039	30.0	810	4.6722	0.5778
0.023	31.0	837	4.3620	0.5556
0.0011	32.0	864	4.9095	0.5556
0.0004	33.0	891	4.8409	0.5333
0.0003	34.0	918	5.0267	0.5556
0.0001	35.0	945	5.0410	0.5556
0.0001	36.0	972	5.0651	0.5556
0.0001	37.0	999	5.0839	0.5556
0.0001	38.0	1026	5.0966	0.5556
0.0001	39.0	1053	5.1068	0.5556
0.0	40.0	1080	5.1156	0.5556
0.0001	41.0	1107	5.1226	0.5556
0.0001	42.0	1134	5.1286	0.5556
0.0001	43.0	1161	5.1335	0.5556
0.0	44.0	1188	5.1362	0.5556
0.0	45.0	1215	5.1386	0.5556
0.0001	46.0	1242	5.1410	0.5556
0.0	47.0	1269	5.1424	0.5556
0.0001	48.0	1296	5.1428	0.5556
0.0	49.0	1323	5.1428	0.5556
0.0001	50.0	1350	5.1428	0.5556

Framework versions

• Transformers 4.35.2
• Pytorch 2.1.0+cu118
• Datasets 2.15.0
• Tokenizers 0.15.0