metadata

library_name: transformers
license: other
base_model: Qwen/qwen-32b-instruct
tags:
  - llama-factory
  - full
  - generated_from_trainer
model-index:
  - name: s1_32b_noq
    results: []

s1_32b_noq

This model is a fine-tuned version of qwen-32b-instruct on the S1_QFFT 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: 1e-05
train_batch_size: 1
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 64
total_eval_batch_size: 64
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: 0.05
num_epochs: 20

Training results

Framework versions

Transformers 4.48.2
Pytorch 2.6.0+cu124
Datasets 3.2.0
Tokenizers 0.21.0

📖 Citation

@misc{liu2025qfft,
  title={QFFT, Question-Free Fine-Tuning for Adaptive Reasoning},
  author={Wanlong Liu and Junxiao Xu and Fei Yu and Yukang Lin and Ke Ji and Wenyu Chen and Yan Xu and Yasheng Wang and Lifeng Shang and Benyou Wang},
  year={2025},
  eprint={2506.12860},
  archivePrefix={arXiv},
  primaryClass={cs.CL},
  url={https://arxiv.org/abs/2506.12860},
}