Model Overview

This model, sft-router-qwen3-4b-swe-bench, is a specialized fine-tuned version of the Qwen/Qwen3-4B base model, developed by JetBrains-Research. It features 4 billion parameters and was trained on the sft_router_train dataset.

Performance Highlights

During its evaluation, the model demonstrated strong performance:

• Loss: 0.0374
• Accuracy: 0.9826

Training Details

The model was trained using specific hyperparameters to achieve its performance:

• Learning Rate: 5e-06
• Batch Size: 4 (train), 4 (eval)
• Gradient Accumulation Steps: 2
• Optimizer: ADAMW_TORCH
• LR Scheduler: Cosine with 100 warmup steps
• Epochs: 2.0

This fine-tuning process aims to adapt the Qwen3-4B architecture for particular tasks, as indicated by its high accuracy on the evaluation set. Further details on intended uses, limitations, and specific training/evaluation data are not provided in the current model card.