transformers pytorch gpt_neox text-generation causal-lm pythia en dataset:Anthropic/hh-rlhf arxiv:2101.00027 license:apache-2.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
datasets:
- Anthropic/hh-rlhf
language:
- en
license: apache-2.0
tags:
- pytorch
- causal-lm
- pythia
---

[Pythia-1b](https://huggingface.co/EleutherAI/pythia-1b) DPO 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/0mhjakjz)

See [Pythia-1b](https://huggingface.co/EleutherAI/pythia-1b) 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-1b-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            | 0.2602|±  |0.0128|
|              |       |none  |     0|acc_norm       | 0.2867|±  |0.0132|
|arc_easy      |      1|none  |     0|acc            | 0.5859|±  |0.0101|
|              |       |none  |     0|acc_norm       | 0.5008|±  |0.0103|
|boolq         |      2|none  |     0|acc            | 0.6205|±  |0.0085|
|hellaswag     |      1|none  |     0|acc            | 0.3895|±  |0.0049|
|              |       |none  |     0|acc_norm       | 0.4872|±  |0.0050|
|lambada_openai|      1|none  |     0|perplexity     | 6.9417|±  |0.2019|
|              |       |none  |     0|acc            | 0.5550|±  |0.0069|
|openbookqa    |      1|none  |     0|acc            | 0.2140|±  |0.0184|
|              |       |none  |     0|acc_norm       | 0.3220|±  |0.0209|
|piqa          |      1|none  |     0|acc            | 0.7193|±  |0.0105|
|              |       |none  |     0|acc_norm       | 0.7008|±  |0.0107|
|sciq          |      1|none  |     0|acc            | 0.8450|±  |0.0115|
|              |       |none  |     0|acc_norm       | 0.7600|±  |0.0135|
|wikitext      |      2|none  |     0|word_perplexity|17.2316|±  |N/A   |
|              |       |none  |     0|byte_perplexity| 1.7029|±  |N/A   |
|              |       |none  |     0|bits_per_byte  | 0.7680|±  |N/A   |
|winogrande    |      1|none  |     0|acc            | 0.5367|±  |0.0140|

hf (pretrained=lomahony/pythia-1b-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            | 0.2662|±  |0.0129|
|              |       |none  |     5|acc_norm       | 0.3003|±  |0.0134|
|arc_easy      |      1|none  |     5|acc            | 0.6103|±  |0.0100|
|              |       |none  |     5|acc_norm       | 0.5892|±  |0.0101|
|boolq         |      2|none  |     5|acc            | 0.6284|±  |0.0085|
|hellaswag     |      1|none  |     5|acc            | 0.3841|±  |0.0049|
|              |       |none  |     5|acc_norm       | 0.4845|±  |0.0050|
|lambada_openai|      1|none  |     5|perplexity     | 9.6301|±  |0.2809|
|              |       |none  |     5|acc            | 0.4865|±  |0.0070|
|openbookqa    |      1|none  |     5|acc            | 0.2020|±  |0.0180|
|              |       |none  |     5|acc_norm       | 0.3300|±  |0.0210|
|piqa          |      1|none  |     5|acc            | 0.7122|±  |0.0106|
|              |       |none  |     5|acc_norm       | 0.7046|±  |0.0106|
|sciq          |      1|none  |     5|acc            | 0.9030|±  |0.0094|
|              |       |none  |     5|acc_norm       | 0.8980|±  |0.0096|
|wikitext      |      2|none  |     5|word_perplexity|17.2316|±  |N/A   |
|              |       |none  |     5|byte_perplexity| 1.7029|±  |N/A   |
|              |       |none  |     5|bits_per_byte  | 0.7680|±  |N/A   |
|winogrande    |      1|none  |     5|acc            | 0.5296|±  |0.0140|

