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:

eval_loss: 2.4052
eval_model_preparation_time: 0.0118
eval_accuracy: 0.1337
eval_runtime: 253.0403
eval_samples_per_second: 10.67
eval_steps_per_second: 0.336
step: 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: 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

Framework versions

Transformers 4.45.2
Pytorch 2.4.1
Datasets 3.0.1
Tokenizers 0.20.1

vony227/vit-base-patch16-224-finetuned-eurosat

vit-base-patch16-224-finetuned-eurosat

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Framework versions

vony227/
vit-base-patch16-224-finetuned-eurosat