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Qwen2.5-VL-7B-real-lora_rank128 – AI Model by ch-min | AlphaNeural AI
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ch-min
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Qwen2.5-VL-7B-real-lora_rank128
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peft
safetensors
llama-factory
lora
generated_from_trainer
Qwen/Qwen2.5-VL-7B-Instruct
adapter
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real-lora_rank128
This model is a fine-tuned version of
Qwen/Qwen2.5-VL-7B-Instruct
on the real_80k 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
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
total_train_batch_size: 32
total_eval_batch_size: 32
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: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3.0
Training results
Framework versions
PEFT 0.15.2
Transformers 4.55.0
Pytorch 2.6.0+cu124
Datasets 3.6.0
Tokenizers 0.21.1
