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vit-base-trees – AI Model by SaeedAnas | AlphaNeural AI
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vit-base-trees
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transformers
pytorch
vit
image-classification
generated_from_trainer
imagefolder
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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vit-base-trees
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on the trees dataset. It achieves the following results on the evaluation set:
Loss: 0.0054
Accuracy: 1.0
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: 0.0002
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
Training results
Framework versions
Transformers 4.29.2
Pytorch 2.0.1
Datasets 2.12.0
Tokenizers 0.13.3
