qwen2.5-coder-7b-securecode

This model is a fine-tuned version of Qwen/Qwen2.5-Coder-7B-Instruct on the securecode-v2 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: 8
• total_train_batch_size: 16
• optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 100
• num_epochs: 3

Training results

Framework versions

• PEFT 0.18.1
• Transformers 4.57.6
• Pytorch 2.7.1+cu128
• Datasets 2.16.0
• Tokenizers 0.22.2