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VLU_vqa_rad – AI Model by aizanzafar | AlphaNeural AI

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aizanzafar/
VLU_vqa_rad

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meta-llama/Llama-3.2-11B-Vision-Instruct

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VLU_vqa_rad

This model is a fine-tuned version of meta-llama/Llama-3.2-11B-Vision-Instruct 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: 0.0002
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 4
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.03
num_epochs: 5

Training results

Framework versions

PEFT 0.13.0
Transformers 4.45.1
Pytorch 2.5.1+cu124
Datasets 3.0.1
Tokenizers 0.20.3