SFT_think_answer

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SFT_think_answer

This model is a fine-tuned version of Qwen/Qwen2.5-VL-3B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0003

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: 1e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• distributed_type: multi-GPU
• num_devices: 2
• gradient_accumulation_steps: 16
• total_train_batch_size: 32
• total_eval_batch_size: 2
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.05
• num_epochs: 3

Training results

Framework versions

• PEFT 0.19.1
• Transformers 5.10.2
• Pytorch 2.12.0+cu126
• Datasets 5.0.0
• Tokenizers 0.22.2