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vit_model – AI Model by Santici | AlphaNeural AI
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Santici
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vit_model
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transformers
pytorch
tensorboard
vit
image-classification
generated_from_trainer
beans
model-index
autotrain_compatible
endpoints_compatible
us
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vit_model
This model is a fine-tuned version of
openai/clip-vit-large-patch14
on the beans dataset. It achieves the following results on the evaluation set:
Loss: 0.7391
Accuracy: 0.6842
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
0.9935
3.85
500
0.7391
0.6842
Framework versions
Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3
