Quantization made by Richard Erkhov. [Github](https://github.com/RichardErkhov) [Discord](https://discord.gg/pvy7H8DZMG) [Request more models](https://github.com/RichardErkhov/quant_request) Gemma-2-9B-It-SPPO-Iter3 - GGUF - Model creator: https://huggingface.co/UCLA-AGI/ - Original model: https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3/ | Name | Quant method | Size | | ---- | ---- | ---- | | [Gemma-2-9B-It-SPPO-Iter3.Q2_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q2_K.gguf) | Q2_K | 3.54GB | | [Gemma-2-9B-It-SPPO-Iter3.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.IQ3_XS.gguf) | IQ3_XS | 3.86GB | | [Gemma-2-9B-It-SPPO-Iter3.IQ3_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.IQ3_S.gguf) | IQ3_S | 4.04GB | | [Gemma-2-9B-It-SPPO-Iter3.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q3_K_S.gguf) | Q3_K_S | 4.04GB | | [Gemma-2-9B-It-SPPO-Iter3.IQ3_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.IQ3_M.gguf) | IQ3_M | 4.19GB | | [Gemma-2-9B-It-SPPO-Iter3.Q3_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q3_K.gguf) | Q3_K | 4.43GB | | [Gemma-2-9B-It-SPPO-Iter3.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q3_K_M.gguf) | Q3_K_M | 4.43GB | | [Gemma-2-9B-It-SPPO-Iter3.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q3_K_L.gguf) | Q3_K_L | 4.78GB | | [Gemma-2-9B-It-SPPO-Iter3.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.IQ4_XS.gguf) | IQ4_XS | 4.86GB | | [Gemma-2-9B-It-SPPO-Iter3.Q4_0.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q4_0.gguf) | Q4_0 | 5.07GB | | [Gemma-2-9B-It-SPPO-Iter3.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.IQ4_NL.gguf) | IQ4_NL | 5.1GB | | [Gemma-2-9B-It-SPPO-Iter3.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q4_K_S.gguf) | Q4_K_S | 5.1GB | | [Gemma-2-9B-It-SPPO-Iter3.Q4_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q4_K.gguf) | Q4_K | 5.37GB | | [Gemma-2-9B-It-SPPO-Iter3.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q4_K_M.gguf) | Q4_K_M | 5.37GB | | [Gemma-2-9B-It-SPPO-Iter3.Q4_1.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q4_1.gguf) | Q4_1 | 5.55GB | | [Gemma-2-9B-It-SPPO-Iter3.Q5_0.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q5_0.gguf) | Q5_0 | 6.04GB | | [Gemma-2-9B-It-SPPO-Iter3.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q5_K_S.gguf) | Q5_K_S | 6.04GB | | [Gemma-2-9B-It-SPPO-Iter3.Q5_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q5_K.gguf) | Q5_K | 6.19GB | | [Gemma-2-9B-It-SPPO-Iter3.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q5_K_M.gguf) | Q5_K_M | 6.19GB | | [Gemma-2-9B-It-SPPO-Iter3.Q5_1.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q5_1.gguf) | Q5_1 | 6.52GB | | [Gemma-2-9B-It-SPPO-Iter3.Q6_K.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q6_K.gguf) | Q6_K | 7.07GB | | [Gemma-2-9B-It-SPPO-Iter3.Q8_0.gguf](https://huggingface.co/RichardErkhov/UCLA-AGI_-_Gemma-2-9B-It-SPPO-Iter3-gguf/blob/main/Gemma-2-9B-It-SPPO-Iter3.Q8_0.gguf) | Q8_0 | 9.15GB | Original model description: --- license: gemma datasets: - openbmb/UltraFeedback language: - en pipeline_tag: text-generation --- Self-Play Preference Optimization for Language Model Alignment (https://arxiv.org/abs/2405.00675) # Gemma-2-9B-It-SPPO-Iter3 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. **Terms of Use**: [Terms](https://www.kaggle.com/models/google/gemma/license/consent/verify/huggingface?returnModelRepoId=google/gemma-2-9b-it) ## Links to Other Models - [Gemma-2-9B-It-SPPO-Iter1](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter1) - [Gemma-2-9B-It-SPPO-Iter2](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2) - [Gemma-2-9B-It-SPPO-Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3) ### Model Description - Model type: A 8B parameter GPT-like model fine-tuned on synthetic datasets. - Language(s) (NLP): Primarily English - License: Apache-2.0 - Finetuned from model: google/gemma-2-9b-it ## [AlpacaEval Leaderboard Evaluation Results](https://tatsu-lab.github.io/alpaca_eval/) | Model | LC. Win Rate | Win Rate | Avg. Length | |-------------------------------------------|:------------:|:--------:|:-----------:| |[Gemma-2-9B-SPPO Iter1](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter1) |48.70 |40.76 | 1669 |[Gemma-2-9B-SPPO Iter2](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter2) |50.93 | 44.64 | 1759 |[Gemma-2-9B-SPPO Iter3](https://huggingface.co/UCLA-AGI/Gemma-2-9B-It-SPPO-Iter3) |**53.27** |**47.74** | 1803 ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-07 - eta: 1000 - per_device_train_batch_size: 8 - gradient_accumulation_steps: 1 - seed: 42 - distributed_type: deepspeed_zero3 - num_devices: 8 - optimizer: RMSProp - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_train_epochs: 1.0 ## Citation ``` @misc{wu2024self, title={Self-Play Preference Optimization for Language Model Alignment}, author={Wu, Yue and Sun, Zhiqing and Yuan, Huizhuo and Ji, Kaixuan and Yang, Yiming and Gu, Quanquan}, year={2024}, eprint={2405.00675}, archivePrefix={arXiv}, primaryClass={cs.LG} } ```