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vit-base-patch16-224-finetuned-eurosat – AI Model by alexavsatov | AlphaNeural AI
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vit-base-patch16-224-finetuned-eurosat
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transformers
tensorboard
safetensors
vit
image-classification
generated_from_trainer
food101
google/vit-base-patch16-224
finetune
model-index
autotrain_compatible
endpoints_compatible
us
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vit-base-patch16-224-finetuned-eurosat
This model is a fine-tuned version of
google/vit-base-patch16-224
on the food101 dataset. It achieves the following results on the evaluation set:
Loss: 0.6541
Accuracy: 0.8389
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: 64
eval_batch_size: 64
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 256
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
1.0843
1.0
266
0.9241
0.7967
0.8596
2.0
533
0.7022
0.8322
0.6834
2.99
798
0.6541
0.8389
Framework versions
Transformers 4.35.2
Pytorch 2.0.1+cu118
Datasets 2.15.0
Tokenizers 0.15.0
