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sbaner24/
vit-base-patch16-224-Trial006_007_008-YEL_STEM

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vit-base-patch16-224-Trial006_007_008-YEL_STEM

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

Loss: 0.0487
Accuracy: 1.0

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: 5e-05
train_batch_size: 30
eval_batch_size: 30
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 120
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
0.7096	0.95	5	0.6879	0.5507
0.6238	1.9	10	0.5505	0.7681
0.4679	2.86	15	0.4054	0.9130
0.3643	4.0	21	0.2855	0.8841
0.3742	4.95	26	0.1808	0.9420
0.2924	5.9	31	0.1566	0.9420
0.2591	6.86	36	0.2318	0.8841
0.3206	8.0	42	0.3704	0.8261
0.1952	8.95	47	0.2086	0.9130
0.2185	9.9	52	0.1194	0.9565
0.2045	10.86	57	0.1291	0.9420
0.2793	12.0	63	0.0912	0.9565
0.2701	12.95	68	0.1109	0.9420
0.266	13.9	73	0.0927	0.9565
0.1964	14.86	78	0.0575	0.9710
0.218	16.0	84	0.0378	0.9855
0.2894	16.95	89	0.0659	0.9710
0.171	17.9	94	0.0706	0.9710
0.1871	18.86	99	0.0845	0.9565
0.2023	20.0	105	0.0487	1.0
0.1707	20.95	110	0.0496	0.9710
0.1741	21.9	115	0.1078	0.9420
0.1391	22.86	120	0.0740	0.9565
0.1892	24.0	126	0.0581	0.9710
0.1488	24.95	131	0.0833	0.9710
0.2089	25.9	136	0.0375	0.9855
0.1922	26.86	141	0.0267	0.9855
0.2222	28.0	147	0.0196	1.0
0.1567	28.95	152	0.0213	0.9855
0.2429	29.9	157	0.0263	1.0
0.1175	30.86	162	0.0304	0.9855
0.1492	32.0	168	0.0291	1.0
0.1401	32.95	173	0.0226	0.9855
0.1757	33.9	178	0.0302	0.9855
0.1773	34.86	183	0.0220	0.9855
0.193	36.0	189	0.0349	0.9855
0.1634	36.95	194	0.0483	0.9855
0.1847	37.9	199	0.0391	0.9855
0.1632	38.86	204	0.0457	0.9855
0.1349	40.0	210	0.0366	0.9855
0.1935	40.95	215	0.0301	0.9855
0.1461	41.9	220	0.0291	0.9855
0.2092	42.86	225	0.0367	0.9855
0.1552	44.0	231	0.0296	0.9855
0.2361	44.95	236	0.0323	0.9855
0.1161	45.9	241	0.0348	0.9855
0.127	46.86	246	0.0365	0.9855
0.186	47.62	250	0.0374	0.9855

Framework versions

Transformers 4.30.0.dev0
Pytorch 1.12.1
Datasets 2.12.0
Tokenizers 0.13.1

sbaner24/vit-base-patch16-224-Trial006_007_008-YEL_STEM

vit-base-patch16-224-Trial006_007_008-YEL_STEM

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sbaner24/
vit-base-patch16-224-Trial006_007_008-YEL_STEM