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

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

vit-base-patch16-224-in21k-finetuned-lora-food101 is a machine learning model from RiniPL. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

License: apache-2.0
Access: Public
Created: Jul 11, 2024
Updated: Jul 13, 2024
SHA: 33e0ba03

Datasets

food101

Model card

From the Hugging Face model README

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: 0.1448
Accuracy: 0.96

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: 0.005
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: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	9	0.5069	0.896
2.1627	2.0	18	0.1891	0.946
0.3451	3.0	27	0.1448	0.96
0.2116	4.0	36	0.1509	0.958
0.1711	5.0	45	0.1498	0.958

Framework versions

Transformers 4.26.0
Pytorch 1.13.1+cu116
Datasets 2.9.0
Tokenizers 0.13.2

License: apache-2.0
Created: Jul 11, 2024
Updated: Jul 13, 2024