hushem_5x_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: 1.4657
• Accuracy: 0.2857

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
1.5422	1.0	28	1.4834	0.2619
1.6237	2.0	56	1.4826	0.2619
1.5562	3.0	84	1.4817	0.2619
1.5833	4.0	112	1.4810	0.2619
1.5467	5.0	140	1.4803	0.2619
1.5372	6.0	168	1.4795	0.2857
1.5683	7.0	196	1.4788	0.2857
1.5057	8.0	224	1.4781	0.2857
1.5994	9.0	252	1.4774	0.2857
1.5076	10.0	280	1.4768	0.2857
1.5466	11.0	308	1.4762	0.2857
1.544	12.0	336	1.4756	0.2857
1.5866	13.0	364	1.4750	0.2857
1.5384	14.0	392	1.4744	0.2857
1.6111	15.0	420	1.4739	0.2857
1.5625	16.0	448	1.4733	0.2857
1.547	17.0	476	1.4728	0.2857
1.5362	18.0	504	1.4723	0.2857
1.5318	19.0	532	1.4718	0.2857
1.5453	20.0	560	1.4714	0.2857
1.5434	21.0	588	1.4709	0.2857
1.548	22.0	616	1.4705	0.2857
1.5105	23.0	644	1.4701	0.2857
1.5176	24.0	672	1.4697	0.2857
1.5194	25.0	700	1.4694	0.2857
1.5543	26.0	728	1.4690	0.2857
1.5727	27.0	756	1.4687	0.2857
1.5476	28.0	784	1.4684	0.2857
1.5163	29.0	812	1.4681	0.2857
1.4767	30.0	840	1.4678	0.2857
1.5623	31.0	868	1.4676	0.2857
1.4924	32.0	896	1.4674	0.2857
1.5673	33.0	924	1.4672	0.2857
1.4842	34.0	952	1.4670	0.2857
1.4908	35.0	980	1.4668	0.2857
1.5184	36.0	1008	1.4666	0.2857
1.5315	37.0	1036	1.4664	0.2857
1.4892	38.0	1064	1.4663	0.2857
1.5241	39.0	1092	1.4662	0.2857
1.5587	40.0	1120	1.4661	0.2857
1.5867	41.0	1148	1.4660	0.2857
1.5357	42.0	1176	1.4659	0.2857
1.479	43.0	1204	1.4659	0.2857
1.4798	44.0	1232	1.4658	0.2857
1.5998	45.0	1260	1.4658	0.2857
1.5487	46.0	1288	1.4658	0.2857
1.5234	47.0	1316	1.4657	0.2857
1.5142	48.0	1344	1.4657	0.2857
1.5259	49.0	1372	1.4657	0.2857
1.5344	50.0	1400	1.4657	0.2857

Framework versions

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