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Rish74/
vit-food101-finetuned

google/vit-base-patch16-224-in21k

apache-2.0

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vit-food101-finetuned

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

Loss: 0.9879
Accuracy: 0.8124

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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
2.6891	1.0	1184	2.5380	0.6677
1.5621	2.0	2368	1.4853	0.7644
1.1777	3.0	3552	1.1228	0.8017
1.1765	4.0	4736	1.0014	0.8142
1.1515	5.0	5920	0.9879	0.8124

Framework versions

PEFT 0.19.1
Transformers 5.0.0
Pytorch 2.11.0+cu128
Datasets 4.0.0
Tokenizers 0.22.2

Rish74/vit-food101-finetuned

vit-food101-finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Rish74/
vit-food101-finetuned