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vit-ena24 – AI Model by Pamreth | AlphaNeural AI
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Pamreth
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vit-ena24
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transformers
tensorboard
safetensors
vit
image-classification
generated_from_trainer
google/vit-base-patch16-224-in21k
finetune
apache-2.0
autotrain_compatible
endpoints_compatible
us
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vit-ena24
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:
eval_loss: 3.0899
eval_model_preparation_time: 0.0031
eval_accuracy: 0.0435
eval_runtime: 925.7714
eval_samples_per_second: 1.415
eval_steps_per_second: 0.177
step: 0
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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 2
mixed_precision_training: Native AMP
Framework versions
Transformers 4.51.1
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1
