--- license: mit datasets: - UCLA-AGI/SPIN_iter1 language: - en base_model: alignment-handbook/zephyr-7b-sft-full pipeline_tag: text-generation --- Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models (https://arxiv.org/abs/2401.01335) # zephyr-7b-sft-full-spin-iter1 This model is a self-play fine-tuned model at iteration 1 from [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) using synthetic data based on on the [HuggingFaceH4/ultrachat_200k](https://huggingface.co/datasets/HuggingFaceH4/ultrachat_200k) dataset. ## Model Details ### Model Description - Model type: A 7B parameter GPT-like model fine-tuned on synthetic datasets. - Language(s) (NLP): Primarily English - License: MIT - Finetuned from model: alignment-handbook/zephyr-7b-sft-full (based on mistralai/Mistral-7B-v0.1) ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-07 - train_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - total_train_batch_size: 64 - optimizer: RMSProp - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 2.0 ## [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_UCLA-AGI__zephyr-7b-sft-full-spin-iter1) | Metric | Value | |-----------------------|---------------------------| | Avg. | 62.86 | | ARC (25-shot) | 65.87 | | HellaSwag (10-shot) | 85.44 | | MMLU (5-shot) | 60.95 | | TruthfulQA (0-shot) | 57.39 | | Winogrande (5-shot) | 76.64 | | GSM8K (5-shot) | 30.86 | ## Citation ``` @misc{chen2024selfplay, title={Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models}, author={Zixiang Chen and Yihe Deng and Huizhuo Yuan and Kaixuan Ji and Quanquan Gu}, year={2024}, eprint={2401.01335}, archivePrefix={arXiv}, primaryClass={cs.LG} } ```