This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.1890
Accuracy: 0.9885

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: 0.0005
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	0.97	21	3.2699	0.6210
No log	1.98	43	2.0011	0.8468
3.1155	2.99	65	1.2851	0.8641
3.1155	4.0	87	0.7751	0.9389
1.1003	4.97	108	0.6060	0.9274
1.1003	5.98	130	0.4584	0.9378
0.5229	6.99	152	0.3417	0.9585
0.5229	8.0	174	0.2415	0.9816
0.5229	8.97	195	0.2014	0.9873
0.3249	9.66	210	0.1890	0.9885

Framework versions

Transformers 4.34.1
Pytorch 1.14.0a0+410ce96
Datasets 2.14.6
Tokenizers 0.14.1

emaeon/vit-base-patch16-224-in21k-finetuned-gecko

vit-base-patch16-224-in21k-finetuned-gecko

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

emaeon/
vit-base-patch16-224-in21k-finetuned-gecko