Model save

README.md

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+---
+base_model: XueyingJia/Qwen2-1.5B-Instruct-oaif
+library_name: transformers
+model_name: Qwen2-1.5B-Instruct-oaif-2-epoch
+tags:
+- generated_from_trainer
+- trl
+- online-dpo
+licence: license
+---
+
+# Model Card for Qwen2-1.5B-Instruct-oaif-2-epoch
+
+This model is a fine-tuned version of [XueyingJia/Qwen2-1.5B-Instruct-oaif](https://huggingface.co/XueyingJia/Qwen2-1.5B-Instruct-oaif).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="XueyingJia/Qwen2-1.5B-Instruct-oaif-2-epoch", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/yujiagao-carnegie-mellon-university/huggingface/runs/9l12wfeq)
+
+This model was trained with Online DPO, a method introduced in [Direct Language Model Alignment from Online AI Feedback](https://huggingface.co/papers/2402.04792).
+
+### Framework versions
+
+- TRL: 0.13.0.dev0
+- Transformers: 4.46.3
+- Pytorch: 2.5.1
+- Datasets: 3.1.0
+- Tokenizers: 0.20.3
+
+## Citations
+
+Cite Online DPO as:
+
+```bibtex
+@article{guo2024direct,
+    title        = {{Direct Language Model Alignment from Online AI Feedback}},
+    author       = {Shangmin Guo and Biao Zhang and Tianlin Liu and Tianqi Liu and Misha Khalman and Felipe Llinares and Alexandre Ram{'{e}} and Thomas Mesnard and Yao Zhao and Bilal Piot and Johan Ferret and Mathieu Blondel},
+    year         = 2024,
+    eprint       = {arXiv:2402.04792}
+}
+```
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

runs/Dec12_01-23-10_babel-0-31/events.out.tfevents.1733984597.babel-0-31.1392139.0

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