vit-ori-dataset-exp – AI Model by sharren | AlphaNeural AI

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sharren/
vit-ori-dataset-exp

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image-classification

generated_from_trainer

google/vit-base-patch16-224

autotrain_compatible

endpoints_compatible

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vit-ori-dataset-exp

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

Loss: 0.6257
Accuracy: 0.8506

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: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6531	0.31	100	0.6383	0.7718
0.6366	0.62	200	0.8169	0.7302
0.7064	0.93	300	0.6012	0.7840
0.4821	1.25	400	0.8299	0.7063
0.474	1.56	500	0.6822	0.7885
0.3619	1.87	600	0.5275	0.8076
0.1723	2.18	700	0.6328	0.7868
0.2579	2.49	800	0.5694	0.8121
0.1422	2.8	900	0.6486	0.8245
0.0528	3.12	1000	0.5941	0.8398
0.0203	3.43	1100	0.6370	0.8502
0.011	3.74	1200	0.6257	0.8506

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2