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vit-base-patch16-224-in21k-finetuned-lora – AI Model by sajjadi | AlphaNeural AI
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sajjadi
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vit-base-patch16-224-in21k-finetuned-lora
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peft
safetensors
generated_from_trainer
google/vit-base-patch16-224-in21k
adapter
apache-2.0
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vit-base-patch16-224-in21k-finetuned-lora
This model is a fine-tuned version of
google/vit-base-patch16-224-in21k
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: 0.005
train_batch_size: 16
eval_batch_size: 16
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Accuracy
No log
1.0
1
4.4977
0.0
Framework versions
PEFT 0.13.0
Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0
