metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - food101
metrics:
  - accuracy
model-index:
  - name: vit-base-patch16-224-in21k-finetuned-lora-food101
    results: []

vit-base-patch16-224-in21k-finetuned-lora-food101

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: 4.0652
Accuracy: 0.74

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: 0.0005
train_batch_size: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 512
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	9	4.2354	0.64
4.4352	2.0	18	4.0652	0.74

Framework versions

Transformers 4.29.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3