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vit-base-patch16-224-v17_4e – AI Model by pphildan | AlphaNeural AI
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pphildan
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vit-base-patch16-224-v17_4e
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-base-patch16-224-v17_4e
This model is a fine-tuned version of
google/vit-base-patch16-224
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0339
Accuracy: 0.9885
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: 0.0005
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: 4
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.2256
1.0
190
0.0818
0.9730
0.1295
2.0
380
0.0581
0.98
0.0901
3.0
570
0.0454
0.9867
0.0666
4.0
760
0.0339
0.9885
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Tokenizers 0.13.3
