This model is a fine-tuned version of google/vit-base-patch16-224-in21k on the food101 dataset. It achieves the following results on the evaluation set:

Loss: 1.5746
Accuracy: 0.894

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.6455	0.99	62	2.4448	0.841
1.751	2.0	125	1.7416	0.879
1.5345	2.98	186	1.5746	0.894

Framework versions

Transformers 4.28.1
Pytorch 1.12.1+cu116
Datasets 2.4.0
Tokenizers 0.12.1

drewglass/results

results

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

drewglass/
results