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vit-base-patch16-224-v23 – AI Model by pphildan | AlphaNeural AI
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pphildan
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vit-base-patch16-224-v23
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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-v23
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: 0.0692
Accuracy: 0.9770
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: 3
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1353
1.0
190
0.1414
0.9511
0.0729
2.0
380
0.0934
0.9685
0.0325
3.0
570
0.0692
0.9770
Framework versions
Transformers 4.29.2
Pytorch 2.0.1+cu118
Tokenizers 0.13.3
