hushem_5x_beit_base_sgd_00001_fold5

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

• Loss: 1.6137
• Accuracy: 0.2439

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
1.5748	1.0	28	1.6349	0.2439
1.5498	2.0	56	1.6339	0.2439
1.5458	3.0	84	1.6329	0.2439
1.5997	4.0	112	1.6319	0.2439
1.5518	5.0	140	1.6310	0.2439
1.6078	6.0	168	1.6301	0.2439
1.6054	7.0	196	1.6292	0.2439
1.5635	8.0	224	1.6284	0.2439
1.5412	9.0	252	1.6276	0.2439
1.5684	10.0	280	1.6268	0.2439
1.5211	11.0	308	1.6261	0.2439
1.5857	12.0	336	1.6254	0.2439
1.5804	13.0	364	1.6248	0.2439
1.5778	14.0	392	1.6241	0.2439
1.5905	15.0	420	1.6235	0.2439
1.5552	16.0	448	1.6228	0.2439
1.5712	17.0	476	1.6222	0.2439
1.5113	18.0	504	1.6216	0.2439
1.5441	19.0	532	1.6210	0.2439
1.547	20.0	560	1.6205	0.2439
1.5712	21.0	588	1.6200	0.2439
1.595	22.0	616	1.6195	0.2439
1.6001	23.0	644	1.6190	0.2439
1.6008	24.0	672	1.6185	0.2439
1.5469	25.0	700	1.6181	0.2439
1.567	26.0	728	1.6177	0.2439
1.618	27.0	756	1.6173	0.2439
1.4849	28.0	784	1.6170	0.2439
1.5706	29.0	812	1.6166	0.2439
1.5269	30.0	840	1.6163	0.2439
1.588	31.0	868	1.6160	0.2439
1.5207	32.0	896	1.6157	0.2439
1.5395	33.0	924	1.6155	0.2439
1.5482	34.0	952	1.6152	0.2439
1.6004	35.0	980	1.6150	0.2439
1.5389	36.0	1008	1.6148	0.2439
1.5566	37.0	1036	1.6146	0.2439
1.54	38.0	1064	1.6145	0.2439
1.5715	39.0	1092	1.6143	0.2439
1.5148	40.0	1120	1.6142	0.2439
1.5688	41.0	1148	1.6141	0.2439
1.5803	42.0	1176	1.6140	0.2439
1.5477	43.0	1204	1.6139	0.2439
1.5623	44.0	1232	1.6138	0.2439
1.5648	45.0	1260	1.6137	0.2439
1.5331	46.0	1288	1.6137	0.2439
1.5791	47.0	1316	1.6137	0.2439
1.5282	48.0	1344	1.6137	0.2439
1.5715	49.0	1372	1.6137	0.2439
1.5955	50.0	1400	1.6137	0.2439

Framework versions

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