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: 0.2215
Accuracy: 0.9609

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: 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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.9129	0.9831	29	0.4537	0.9330
0.3054	2.0	59	0.2456	0.9553
0.2369	2.9492	87	0.2215	0.9609

Framework versions

Transformers 4.40.1
Pytorch 2.3.0+cpu
Datasets 2.19.1
Tokenizers 0.19.1

Manuel-O/vit-base-patch16-224-in21k-finetuned-CT

vit-base-patch16-224-in21k-finetuned-CT

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Manuel-O/
vit-base-patch16-224-in21k-finetuned-CT