hushem_5x_deit_tiny_sgd_0001_fold1

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

• Loss: 1.5185
• Accuracy: 0.2667

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: 0.0001
• 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
1.5559	1.0	27	1.6659	0.2667
1.5307	2.0	54	1.6510	0.2667
1.5463	3.0	81	1.6380	0.2889
1.5241	4.0	108	1.6272	0.2889
1.4794	5.0	135	1.6169	0.2889
1.5071	6.0	162	1.6070	0.2889
1.4768	7.0	189	1.5986	0.2889
1.4869	8.0	216	1.5910	0.2889
1.4651	9.0	243	1.5844	0.3111
1.4396	10.0	270	1.5781	0.3111
1.4572	11.0	297	1.5728	0.3111
1.4029	12.0	324	1.5680	0.3111
1.4355	13.0	351	1.5638	0.3111
1.4582	14.0	378	1.5597	0.2889
1.4073	15.0	405	1.5561	0.2889
1.4381	16.0	432	1.5526	0.2889
1.4333	17.0	459	1.5495	0.2889
1.3978	18.0	486	1.5468	0.2889
1.3884	19.0	513	1.5441	0.2889
1.3796	20.0	540	1.5418	0.2889
1.4025	21.0	567	1.5397	0.2889
1.3822	22.0	594	1.5376	0.2889
1.3868	23.0	621	1.5359	0.2889
1.3907	24.0	648	1.5343	0.2889
1.38	25.0	675	1.5327	0.2667
1.3755	26.0	702	1.5313	0.2667
1.3485	27.0	729	1.5299	0.2667
1.3648	28.0	756	1.5287	0.2667
1.3797	29.0	783	1.5276	0.2667
1.3716	30.0	810	1.5265	0.2667
1.389	31.0	837	1.5256	0.2667
1.3813	32.0	864	1.5247	0.2667
1.3289	33.0	891	1.5240	0.2667
1.3517	34.0	918	1.5232	0.2667
1.3834	35.0	945	1.5225	0.2667
1.3458	36.0	972	1.5218	0.2667
1.3745	37.0	999	1.5212	0.2667
1.3761	38.0	1026	1.5207	0.2667
1.3726	39.0	1053	1.5203	0.2667
1.3125	40.0	1080	1.5199	0.2667
1.3599	41.0	1107	1.5196	0.2667
1.3277	42.0	1134	1.5193	0.2667
1.3748	43.0	1161	1.5191	0.2667
1.3689	44.0	1188	1.5188	0.2667
1.3379	45.0	1215	1.5187	0.2667
1.3358	46.0	1242	1.5186	0.2667
1.3497	47.0	1269	1.5185	0.2667
1.3482	48.0	1296	1.5185	0.2667
1.3616	49.0	1323	1.5185	0.2667
1.3216	50.0	1350	1.5185	0.2667

Framework versions

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