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vit-small-patch16-224-finetuned-cifar10 – AI Model by raks87 | AlphaNeural AI
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vit-small-patch16-224-finetuned-cifar10
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transformers
tensorboard
safetensors
vit
image-classification
generated_from_trainer
WinKawaks/vit-small-patch16-224
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-small-patch16-224-finetuned-cifar10
This model is a fine-tuned version of
WinKawaks/vit-small-patch16-224
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.0459
Accuracy: 0.9844
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
0.2682
1.0
390
0.0821
0.9713
0.252
2.0
781
0.0502
0.9842
0.173
2.99
1170
0.0459
0.9844
Framework versions
Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2
