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

Loss: 0.6915
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: 3e-05
train_batch_size: 8
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 16

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1803	1.0	1	0.6093	1.0
0.1831	2.0	2	0.6375	1.0
0.1762	3.0	3	0.6897	1.0
0.1753	4.0	4	0.6915	1.0

Framework versions

Transformers 4.38.1
Pytorch 2.2.1+cpu
Datasets 2.17.1
Tokenizers 0.15.2

Hemg/Chest_Xray

Chest_Xray

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Hemg/
Chest_Xray