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siglip-large-patch16-256-image-sensitivity – AI Model by ljnlonoljpiljm | AlphaNeural AI

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ljnlonoljpiljm/
siglip-large-patch16-256-image-sensitivity

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image-classification

generated_from_trainer

google/siglip-large-patch16-256

autotrain_compatible

endpoints_compatible

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siglip-large-patch16-256-image-sensitivity

This model is a fine-tuned version of google/siglip-large-patch16-256 on an unknown dataset.

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
gradient_accumulation_steps: 16
total_train_batch_size: 512
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: 10
mixed_precision_training: Native AMP

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.21.0