hushem_40x_deit_small_sgd_00001_fold4

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: 1.4814
• Accuracy: 0.2619

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: 1e-05
• 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
1.9934	1.0	219	1.6922	0.2619
1.9676	2.0	438	1.6780	0.2619
1.8623	3.0	657	1.6644	0.2619
1.8471	4.0	876	1.6514	0.2619
1.8032	5.0	1095	1.6391	0.2619
1.7347	6.0	1314	1.6275	0.2619
1.7421	7.0	1533	1.6165	0.2619
1.7487	8.0	1752	1.6060	0.2857
1.7488	9.0	1971	1.5962	0.2857
1.6907	10.0	2190	1.5869	0.2857
1.7571	11.0	2409	1.5783	0.2857
1.7123	12.0	2628	1.5703	0.3095
1.6705	13.0	2847	1.5628	0.3095
1.6677	14.0	3066	1.5558	0.3095
1.7011	15.0	3285	1.5494	0.3095
1.6459	16.0	3504	1.5434	0.3095
1.6424	17.0	3723	1.5379	0.2857
1.666	18.0	3942	1.5328	0.2857
1.5793	19.0	4161	1.5282	0.2857
1.612	20.0	4380	1.5239	0.2857
1.6378	21.0	4599	1.5199	0.2857
1.603	22.0	4818	1.5163	0.2857
1.5587	23.0	5037	1.5130	0.2619
1.5451	24.0	5256	1.5099	0.2619
1.6036	25.0	5475	1.5071	0.2619
1.5234	26.0	5694	1.5045	0.2857
1.5523	27.0	5913	1.5021	0.2857
1.5056	28.0	6132	1.4999	0.2857
1.5455	29.0	6351	1.4979	0.2857
1.5427	30.0	6570	1.4960	0.2857
1.566	31.0	6789	1.4943	0.2857
1.5088	32.0	7008	1.4927	0.2857
1.524	33.0	7227	1.4913	0.2857
1.5159	34.0	7446	1.4900	0.2857
1.4946	35.0	7665	1.4888	0.2619
1.5331	36.0	7884	1.4877	0.2619
1.5143	37.0	8103	1.4867	0.2619
1.5074	38.0	8322	1.4858	0.2619
1.4853	39.0	8541	1.4850	0.2619
1.5395	40.0	8760	1.4843	0.2619
1.4854	41.0	8979	1.4837	0.2619
1.4835	42.0	9198	1.4832	0.2619
1.5069	43.0	9417	1.4827	0.2619
1.4921	44.0	9636	1.4823	0.2619
1.4639	45.0	9855	1.4820	0.2619
1.511	46.0	10074	1.4818	0.2619
1.4986	47.0	10293	1.4816	0.2619
1.4648	48.0	10512	1.4815	0.2619
1.5244	49.0	10731	1.4814	0.2619
1.5102	50.0	10950	1.4814	0.2619

Framework versions

• Transformers 4.32.1
• Pytorch 2.1.0+cu121
• Datasets 2.12.0
• Tokenizers 0.13.2