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--- |
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base_model: UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3 |
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license: gemma |
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datasets: |
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- openbmb/UltraFeedback |
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language: |
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- en |
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pipeline_tag: text-generation |
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quantized_by: harborwater |
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--- |
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# This is a 4bit quantized version of [UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3) |
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Self-Play Preference Optimization for Language Model Alignment (https://arxiv.org/abs/2405.00675) |
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# Gemma-2-9B-It-SPPO-Iter3 |
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This model was developed using [Self-Play Preference Optimization](https://arxiv.org/abs/2405.00675) at iteration 3, based on the [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) architecture as starting point. We utilized the prompt sets from the [openbmb/UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset, splited to 3 parts for 3 iterations by [snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset](https://huggingface.co/datasets/snorkelai/Snorkel-Mistral-PairRM-DPO-Dataset). All responses used are synthetic. |
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**Terms of Use**: [Terms](https://www.kaggle.com/models/google/gemma/license/consent/verify/huggingface?returnModelRepoId=google/gemma-2-9b-it) |
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## Links to Other Models |
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- [Gemma-2-9B-It-SPPO-Iter1](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter1) |
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- [Gemma-2-9B-It-SPPO-Iter2](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2) |
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- [Gemma-2-9B-It-SPPO-Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3) |
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### Model Description |
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- Model type: A 8B parameter GPT-like model fine-tuned on synthetic datasets. |
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- Language(s) (NLP): Primarily English |
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- License: Apache-2.0 |
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- Finetuned from model: google/gemma-2-9b-it |
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## [AlpacaEval Leaderboard Evaluation Results](https://tatsu-lab.github.io/alpaca_eval/) |
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| Model | LC. Win Rate | Win Rate | Avg. Length | |
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|-------------------------------------------|:------------:|:--------:|:-----------:| |
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|[Gemma-2-9B-SPPO Iter1](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter1) |48.70 |40.76 | 1669 |
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|[Gemma-2-9B-SPPO Iter2](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2) |50.93 | 44.64 | 1759 |
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|[Gemma-2-9B-SPPO Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3) |**53.27** |**47.74** | 1803 |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-07 |
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- eta: 1000 |
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- per_device_train_batch_size: 8 |
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- gradient_accumulation_steps: 1 |
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- seed: 42 |
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- distributed_type: deepspeed_zero3 |
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- num_devices: 8 |
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- optimizer: RMSProp |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_train_epochs: 1.0 |
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## Citation |
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``` |
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@misc{wu2024self, |
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title={Self-Play Preference Optimization for Language Model Alignment}, |
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author={Wu, Yue and Sun, Zhiqing and Yuan, Huizhuo and Ji, Kaixuan and Yang, Yiming and Gu, Quanquan}, |
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year={2024}, |
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eprint={2405.00675}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.LG} |
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} |
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``` |
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