---
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- Anthropic/hh-rlhf
---

[Pythia-1b](https://huggingface.co./EleutherAI/pythia-1b) supervised finetuned using TRLx library 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/trlx-pythia/tree/main)

[wandb log](https://wandb.ai/lauraomahony999/sft-pythia/runs/azscanfe)

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-sft), 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            | 0.2543|±  |0.0127|
|              |       |none  |     0|acc_norm       | 0.2739|±  |0.0130|
|arc_easy      |      1|none  |     0|acc            | 0.5724|±  |0.0102|
|              |       |none  |     0|acc_norm       | 0.4941|±  |0.0103|
|boolq         |      2|none  |     0|acc            | 0.6199|±  |0.0085|
|hellaswag     |      1|none  |     0|acc            | 0.3819|±  |0.0048|
|              |       |none  |     0|acc_norm       | 0.4736|±  |0.0050|
|lambada_openai|      1|none  |     0|perplexity     | 7.1374|±  |0.2014|
|              |       |none  |     0|acc            | 0.5626|±  |0.0069|
|openbookqa    |      1|none  |     0|acc            | 0.2040|±  |0.0180|
|              |       |none  |     0|acc_norm       | 0.3140|±  |0.0208|
|piqa          |      1|none  |     0|acc            | 0.7138|±  |0.0105|
|              |       |none  |     0|acc_norm       | 0.6997|±  |0.0107|
|sciq          |      1|none  |     0|acc            | 0.8400|±  |0.0116|
|              |       |none  |     0|acc_norm       | 0.7620|±  |0.0135|
|wikitext      |      2|none  |     0|word_perplexity|16.9719|±  |N/A   |
|              |       |none  |     0|byte_perplexity| 1.6981|±  |N/A   |
|              |       |none  |     0|bits_per_byte  | 0.7639|±  |N/A   |
|winogrande    |      1|none  |     0|acc            | 0.5343|±  |0.0140|

hf (pretrained=lomahony/pythia-1b-helpful-sft), 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            | 0.2628|±  |0.0129|
|              |       |none  |     5|acc_norm       | 0.2918|±  |0.0133|
|arc_easy      |      1|none  |     5|acc            | 0.6040|±  |0.0100|
|              |       |none  |     5|acc_norm       | 0.5816|±  |0.0101|
|boolq         |      2|none  |     5|acc            | 0.5963|±  |0.0086|
|hellaswag     |      1|none  |     5|acc            | 0.3780|±  |0.0048|
|              |       |none  |     5|acc_norm       | 0.4719|±  |0.0050|
|lambada_openai|      1|none  |     5|perplexity     |10.2584|±  |0.2936|
|              |       |none  |     5|acc            | 0.4832|±  |0.0070|
|openbookqa    |      1|none  |     5|acc            | 0.1980|±  |0.0178|
|              |       |none  |     5|acc_norm       | 0.3220|±  |0.0209|
|piqa          |      1|none  |     5|acc            | 0.7057|±  |0.0106|
|              |       |none  |     5|acc_norm       | 0.7095|±  |0.0106|
|sciq          |      1|none  |     5|acc            | 0.8980|±  |0.0096|
|              |       |none  |     5|acc_norm       | 0.9000|±  |0.0095|
|wikitext      |      2|none  |     5|word_perplexity|16.9719|±  |N/A   |
|              |       |none  |     5|byte_perplexity| 1.6981|±  |N/A   |
|              |       |none  |     5|bits_per_byte  | 0.7639|±  |N/A   |
|winogrande    |      1|none  |     5|acc            | 0.5446|±  |0.0140|