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vit-model – AI Model by FelipeMedina16 | AlphaNeural AI
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FelipeMedina16
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vit-model
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
beans
apache-2.0
model-index
autotrain_compatible
endpoints_compatible
us
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vit-model
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
on the beans dataset. It achieves the following results on the evaluation set:
Loss: 0.0297
Accuracy: 0.9925
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: 8
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
Training Loss
Epoch
Step
Validation Loss
Accuracy
0.1385
3.85
500
0.0297
0.9925
Framework versions
Transformers 4.28.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3
