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vit-base-patch16-224-finetuned-eurosat – AI Model by sahild23d23e23re23r | AlphaNeural AI
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sahild23d23e23re23r
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vit-base-patch16-224-finetuned-eurosat
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transformers
pytorch
vit
image-classification
generated_from_trainer
imagefolder
google/vit-base-patch16-224
finetune
apache-2.0
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 imagefolder dataset. It achieves the following results on the evaluation set:
eval_loss: 0.0077
eval_accuracy: 0.9990
eval_runtime: 172.7146
eval_samples_per_second: 50.372
eval_steps_per_second: 1.575
epoch: 1.0
step: 611
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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
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
Framework versions
Transformers 4.34.0
Pytorch 2.1.0
Datasets 2.12.0
Tokenizers 0.14.1
