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vit-base-molecul-v2-5-epoch – AI Model by dyvapandhu | AlphaNeural AI
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dyvapandhu
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vit-base-molecul-v2-5-epoch
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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-molecul-v2-5-epoch
This model is a fine-tuned version of
google/vit-base-patch16-224
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.5290
Accuracy: 0.77
F1: 0.7698
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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
Training results
Framework versions
Transformers 4.31.0.dev0
Pytorch 2.0.1
Datasets 2.13.1
Tokenizers 0.11.0
