lomahony/pythia-70m-helpful-dpo
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: lomahony/pythia-70m-helpful-dpo
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-05-28 09:23:20 +08:00
commit 4108ee03b3
8 changed files with 100907 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

80
README.md Normal file
View File

@@ -0,0 +1,80 @@
---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- Anthropic/hh-rlhf
---
[Pythia-70m](https://huggingface.co/EleutherAI/pythia-70m) finetuned using original DPO code with the helpful subset of [Anthropic-hh-rlhf dataset](https://huggingface.co/datasets/Anthropic/hh-rlhf) for 1 epoch.
Checkpoints are also uploaded.
Fully reproducible finetuning code is available on [GitHub](https://github.com/lauraaisling/direct-preference-optimization/tree/main)
[wandb log](https://wandb.ai/lauraomahony999/pythia-dpo/runs/wc2q2vp1)
See [Pythia-70m](https://huggingface.co/EleutherAI/pythia-70m) for model details [(paper)](https://arxiv.org/abs/2101.00027).
See further details of these models in the paper [Attributing Mode Collapse in the Fine-Tuning of Large Language Models](https://openreview.net/pdf?id=3pDMYjpOxk).
You can cite these models if they are helpful as follows:
<pre>
@inproceedings{o2024attributing,
title={Attributing Mode Collapse in the Fine-Tuning of Large Language Models},
author={O’Mahony, Laura and Grinsztajn, Leo and Schoelkopf, Hailey and Biderman, Stella},
booktitle={ICLR 2024, Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) workshop},
year={2024}
}
</pre>
hf (pretrained=lomahony/pythia-70m-helpful-dpo), gen_kwargs: (None), limit: None, num_fewshot: 0, batch_size: 16
| Tasks |Version|Filter|n-shot| Metric | Value | | Stderr |
|--------------|------:|------|-----:|---------------|--------:|---|--------|
|arc_challenge | 1|none | 0|acc | 0.1724|± | 0.0110|
| | |none | 0|acc_norm | 0.2201|± | 0.0121|
|arc_easy | 1|none | 0|acc | 0.3350|± | 0.0097|
| | |none | 0|acc_norm | 0.3380|± | 0.0097|
|boolq | 2|none | 0|acc | 0.4315|± | 0.0087|
|hellaswag | 1|none | 0|acc | 0.2614|± | 0.0044|
| | |none | 0|acc_norm | 0.2665|± | 0.0044|
|lambada_openai| 1|none | 0|perplexity |5951.7544|± |428.5435|
| | |none | 0|acc | 0.0309|± | 0.0024|
|openbookqa | 1|none | 0|acc | 0.1460|± | 0.0158|
| | |none | 0|acc_norm | 0.2440|± | 0.0192|
|piqa | 1|none | 0|acc | 0.5550|± | 0.0116|
| | |none | 0|acc_norm | 0.5501|± | 0.0116|
|sciq | 1|none | 0|acc | 0.4010|± | 0.0155|
| | |none | 0|acc_norm | 0.5070|± | 0.0158|
|wikitext | 2|none | 0|word_perplexity| 547.6920|± |N/A |
| | |none | 0|byte_perplexity| 3.2518|± |N/A |
| | |none | 0|bits_per_byte | 1.7012|± |N/A |
|winogrande | 1|none | 0|acc | 0.4822|± | 0.0140|
hf (pretrained=lomahony/pythia-70m-helpful-dpo), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 16
| Tasks |Version|Filter|n-shot| Metric | Value | | Stderr |
|--------------|------:|------|-----:|---------------|---------:|---|---------|
|arc_challenge | 1|none | 5|acc | 0.1886|± | 0.0114|
| | |none | 5|acc_norm | 0.2338|± | 0.0124|
|arc_easy | 1|none | 5|acc | 0.3346|± | 0.0097|
| | |none | 5|acc_norm | 0.3308|± | 0.0097|
|boolq | 2|none | 5|acc | 0.4028|± | 0.0086|
|hellaswag | 1|none | 5|acc | 0.2617|± | 0.0044|
| | |none | 5|acc_norm | 0.2648|± | 0.0044|
|lambada_openai| 1|none | 5|perplexity |22676.7987|± |1626.4435|
| | |none | 5|acc | 0.0173|± | 0.0018|
|openbookqa | 1|none | 5|acc | 0.1640|± | 0.0166|
| | |none | 5|acc_norm | 0.2460|± | 0.0193|
|piqa | 1|none | 5|acc | 0.5528|± | 0.0116|
| | |none | 5|acc_norm | 0.5462|± | 0.0116|
|sciq | 1|none | 5|acc | 0.3100|± | 0.0146|
| | |none | 5|acc_norm | 0.4220|± | 0.0156|
|wikitext | 2|none | 5|word_perplexity| 547.6920|± |N/A |
| | |none | 5|byte_perplexity| 3.2518|± |N/A |
| | |none | 5|bits_per_byte | 1.7012|± |N/A |
|winogrande | 1|none | 5|acc | 0.5201|± | 0.0140|