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SmolVLM-Base-vqav2 – AI Model by Ghada-b | AlphaNeural AI
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Ghada-b
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SmolVLM-Base-vqav2
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peft
tensorboard
safetensors
adapter
lora
transformers
HuggingFaceTB/SmolVLM-Base
apache-2.0
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SmolVLM-Base-vqav2
This model is a fine-tuned version of
HuggingFaceTB/SmolVLM-Base
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: 0.0001
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 3
Training results
Framework versions
PEFT 0.18.0
Transformers 4.57.2
Pytorch 2.9.0+cu126
Datasets 4.0.0
Tokenizers 0.22.1
