--- license: mit base_model: ZhangShenao/SELM-Zephyr-7B-iter-2 tags: - alignment-handbook - dpo - trl - selm datasets: - HuggingFaceH4/ultrafeedback_binarized model-index: - name: SELM-Zephyr-7B-iter-3 results: [] --- [Self-Exploring Language Models: Active Preference Elicitation for Online Alignment](https://arxiv.org/abs/2405.19332). # SELM-Zephyr-7B-iter-3 This model is a fine-tuned version of [ZhangShenao/SELM-Zephyr-7B-iter-2](https://huggingface.co/ZhangShenao/SELM-Zephyr-7B-iter-2) using synthetic data based on on the HuggingFaceH4/ultrafeedback_binarized dataset. ## Model description - Model type: A 7B parameter Zephyr-based Self-Exploring Language Models (SELM). - License: MIT ## Results | | AlpacaEval 2.0 (LC WR) | MT-Bench (Average) | |----------------------------------------|------------------------|--------------------| | [SELM-Zephyr-7B-iter-3](https://huggingface.co/ZhangShenao/SELM-Zephyr-7B-iter-3) |        24.00 |       7.48 | | [SELM-Zephyr-7B-iter-2](https://huggingface.co/ZhangShenao/SELM-Zephyr-7B-iter-2) |        23.40 |       7.72 | | [SELM-Zephyr-7B-iter-1](https://huggingface.co/ZhangShenao/SELM-Zephyr-7B-iter-1) |        20.28 |       7.42 | | [DPO-Zephyr-7B](https://huggingface.co/ZhangShenao/DPO-Zephyr-7B) |        14.45 |       7.28 | Our model also ranks highly on [WildBench](https://huggingface.co/spaces/allenai/WildBench)! 🔥 ### Training hyperparameters The following hyperparameters were used during training: - alpha: 0.001 - beta: 0.01 - train_batch_size: 8 - seed: 42 - distributed_type: multi-GPU - num_devices: 8 - gradient_accumulation_steps: 4 - total_train_batch_size: 256 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - num_epochs: 1 ### Framework versions - Transformers 4.40.2 - Pytorch 2.1.2+cu121 - Datasets 2.14.6 - Tokenizers 0.19.1