This model is a fine-tuned version of google/vit-base-patch32-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:

Loss: 1.6175
Accuracy: 0.7321

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
2.6483	1.0	532	2.5574	0.6605
1.8885	2.0	1064	1.8063	0.7182
1.6371	3.0	1596	1.6175	0.7321

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

sshreshtha/vit-base-patch32-224-in21k-finetuned-eurosat

vit-base-patch32-224-in21k-finetuned-eurosat

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

sshreshtha/
vit-base-patch32-224-in21k-finetuned-eurosat