Model Card for Llama 3.1 Tulu V2 8B RM - UltraFeedback
Tulu is a series of language models that are trained to act as helpful assistants.
This is a 8B reward model used for PPO training trained on the UltraFeedback dataset.
Dataset:
Data used to train this model can be found
here
- specifically the
ultrafeedback_mean_aspects
split.
Input Format
The model is trained to use the following format (note the newlines):
<|user|>
Your message here!
<|assistant|>
For best results, format all inputs in this manner.
Make sure to include a newline after
<|assistant|>
, this can affect generation quality quite a bit.
We have included a
chat template
in the tokenizer implementing this template.
Intended uses & limitations
The model was initially fine-tuned on a filtered and preprocessed of the
Tulu V2 mix dataset
, which contains a diverse range of human created instructions and synthetic dialogues generated primarily by other LLMs.
We then further trained the model with a
Jax RM trainer
built on
EasyLM
on the dataset mentioned above.
This model is meant as a research artefact.
Training hyperparameters
The following hyperparameters were used during RM training:
learning_rate: 5e-06
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear cooldown to 0.
lr_scheduler_warmup_ratio: 0.03
num_epochs: 1.0
Citation
If you find Tulu 2.5 is useful in your work, please cite it with:
@misc{ivison2024unpacking,
title={{Unpacking DPO and PPO: Disentangling Best Practices for Learning from Preference Feedback}},
author={{Hamish Ivison and Yizhong Wang and Jiacheng Liu and Ellen Wu and Valentina Pyatkin and Nathan Lambert and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi}}
year={2024},
eprint={2406.09279},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Runs of allenai llama-3.1-tulu-2-8b-uf-mean-rm on huggingface.co
179
Total runs
0
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-93
3-day runs
-104
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-41
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