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: 0.8426
Accuracy: 0.922

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: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.8526	0.992	62	2.6167	0.836
1.7104	2.0	125	1.5818	0.884
1.2318	2.992	187	1.1876	0.915
0.9759	4.0	250	0.9661	0.92
0.8262	4.992	312	0.8780	0.92
0.7681	5.952	372	0.8362	0.93

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

fadhfaiz/reapikui_best_model

reapikui_best_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

fadhfaiz/
reapikui_best_model