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qwen3vl_ins_lora_math_10k – AI Model by UoM-CS-NeuroSymbolicAI | AlphaNeural AI
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qwen3vl_ins_lora_math_10k
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qwen3vl_ins_lora_math
This model is a fine-tuned version of
Qwen/Qwen3-VL-8B-Instruct
on the math_interleave 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: 4
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 2
gradient_accumulation_steps: 2
total_train_batch_size: 16
total_eval_batch_size: 16
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: 2.0
Training results
Framework versions
PEFT 0.18.1
Transformers 4.57.1
Pytorch 2.5.1+cu121
Datasets 4.0.0
Tokenizers 0.22.2