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: 0.7340
Accuracy: 0.825

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: 64
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0481	1.67	10	0.4926	0.825
0.3714	3.33	20	0.3388	0.9
0.0642	5.0	30	0.3255	0.875
0.0199	6.67	40	0.4111	0.875
0.0074	8.33	50	0.3334	0.925
0.0024	10.0	60	0.3710	0.9
0.0131	11.67	70	0.5366	0.85
0.0067	13.33	80	0.5172	0.875
0.0152	15.0	90	0.4835	0.9
0.0058	16.67	100	0.3979	0.875
0.0005	18.33	110	0.5964	0.825
0.0008	20.0	120	0.7340	0.825

Framework versions

Transformers 4.27.3
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2

tcvrishank/histo_train_vit

histo_train_vit

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

tcvrishank/
histo_train_vit