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vit-base-patch16-224-finetuned-vit – AI Model by lizsergeeva | AlphaNeural AI
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lizsergeeva
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vit-base-patch16-224-finetuned-vit
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
imagefolder
google/vit-base-patch16-224
finetune
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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vit-base-patch16-224-finetuned-vit
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:
Loss: 0.2549
Accuracy: 0.9161
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
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.6065
0.99
47
0.4006
0.8748
0.335
2.0
95
0.2745
0.9175
0.2707
2.97
141
0.2549
0.9161
Framework versions
Transformers 4.31.0
Pytorch 2.0.1+cu118
Datasets 2.14.4
Tokenizers 0.13.3
