hushem_5x_deit_tiny_sgd_00001_fold4

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: 1.6392
• 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
1.5126	1.0	28	1.6960	0.2857
1.4875	2.0	56	1.6934	0.2857
1.484	3.0	84	1.6908	0.2857
1.5224	4.0	112	1.6883	0.2857
1.464	5.0	140	1.6861	0.2857
1.514	6.0	168	1.6836	0.2857
1.4795	7.0	196	1.6813	0.2857
1.4849	8.0	224	1.6790	0.2857
1.4832	9.0	252	1.6769	0.2857
1.5231	10.0	280	1.6747	0.2857
1.5146	11.0	308	1.6728	0.2857
1.4709	12.0	336	1.6708	0.2857
1.5002	13.0	364	1.6689	0.2857
1.4731	14.0	392	1.6671	0.2857
1.4733	15.0	420	1.6654	0.2857
1.4938	16.0	448	1.6637	0.2857
1.517	17.0	476	1.6621	0.2857
1.4904	18.0	504	1.6604	0.2857
1.4813	19.0	532	1.6589	0.2857
1.4788	20.0	560	1.6576	0.2857
1.476	21.0	588	1.6562	0.2857
1.5095	22.0	616	1.6550	0.2857
1.4801	23.0	644	1.6537	0.2857
1.4778	24.0	672	1.6525	0.2857
1.4526	25.0	700	1.6513	0.2857
1.4781	26.0	728	1.6502	0.2857
1.4923	27.0	756	1.6492	0.2857
1.4977	28.0	784	1.6482	0.2857
1.4558	29.0	812	1.6472	0.2857
1.4785	30.0	840	1.6464	0.2857
1.4962	31.0	868	1.6455	0.2857
1.4638	32.0	896	1.6447	0.2857
1.5095	33.0	924	1.6440	0.2857
1.4775	34.0	952	1.6433	0.2857
1.4595	35.0	980	1.6427	0.2857
1.4656	36.0	1008	1.6421	0.2857
1.4403	37.0	1036	1.6416	0.2857
1.4824	38.0	1064	1.6412	0.2857
1.5225	39.0	1092	1.6408	0.2857
1.4471	40.0	1120	1.6404	0.2857
1.4797	41.0	1148	1.6401	0.2857
1.4455	42.0	1176	1.6399	0.2857
1.4823	43.0	1204	1.6397	0.2857
1.4547	44.0	1232	1.6395	0.2857
1.4676	45.0	1260	1.6394	0.2857
1.4731	46.0	1288	1.6393	0.2857
1.4786	47.0	1316	1.6393	0.2857
1.4805	48.0	1344	1.6392	0.2857
1.5172	49.0	1372	1.6392	0.2857
1.4525	50.0	1400	1.6392	0.2857

Framework versions

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