transformers pytorch safetensors 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-410m](https://huggingface.co/EleutherAI/pythia-410m) 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/pythia-sft/runs/quq2097z)

See [Pythia-410m](https://huggingface.co/EleutherAI/pythia-410m) 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-410m-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            | 0.2355|±  |0.0124|
|              |       |none  |     0|acc_norm       | 0.2594|±  |0.0128|
|arc_easy      |      1|none  |     0|acc            | 0.5051|±  |0.0103|
|              |       |none  |     0|acc_norm       | 0.4478|±  |0.0102|
|boolq         |      2|none  |     0|acc            | 0.6113|±  |0.0085|
|hellaswag     |      1|none  |     0|acc            | 0.3372|±  |0.0047|
|              |       |none  |     0|acc_norm       | 0.4001|±  |0.0049|
|lambada_openai|      1|none  |     0|perplexity     |21.8172|±  |0.7736|
|              |       |none  |     0|acc            | 0.3755|±  |0.0067|
|openbookqa    |      1|none  |     0|acc            | 0.1940|±  |0.0177|
|              |       |none  |     0|acc_norm       | 0.2960|±  |0.0204|
|piqa          |      1|none  |     0|acc            | 0.6719|±  |0.0110|
|              |       |none  |     0|acc_norm       | 0.6687|±  |0.0110|
|sciq          |      1|none  |     0|acc            | 0.7700|±  |0.0133|
|              |       |none  |     0|acc_norm       | 0.6540|±  |0.0151|
|wikitext      |      2|none  |     0|word_perplexity|23.8136|±  |N/A   |
|              |       |none  |     0|byte_perplexity| 1.8091|±  |N/A   |
|              |       |none  |     0|bits_per_byte  | 0.8553|±  |N/A   |
|winogrande    |      1|none  |     0|acc            | 0.5320|±  |0.0140|

hf (pretrained=lomahony/pythia-410m-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            | 0.2355|±  |0.0124|
|              |       |none  |     5|acc_norm       | 0.2790|±  |0.0131|
|arc_easy      |      1|none  |     5|acc            | 0.5274|±  |0.0102|
|              |       |none  |     5|acc_norm       | 0.5072|±  |0.0103|
|boolq         |      2|none  |     5|acc            | 0.5226|±  |0.0087|
|hellaswag     |      1|none  |     5|acc            | 0.3367|±  |0.0047|
|              |       |none  |     5|acc_norm       | 0.3991|±  |0.0049|
|lambada_openai|      1|none  |     5|perplexity     |37.4791|±  |1.3737|
|              |       |none  |     5|acc            | 0.3049|±  |0.0064|
|openbookqa    |      1|none  |     5|acc            | 0.1620|±  |0.0165|
|              |       |none  |     5|acc_norm       | 0.2900|±  |0.0203|
|piqa          |      1|none  |     5|acc            | 0.6708|±  |0.0110|
|              |       |none  |     5|acc_norm       | 0.6676|±  |0.0110|
|sciq          |      1|none  |     5|acc            | 0.8630|±  |0.0109|
|              |       |none  |     5|acc_norm       | 0.8430|±  |0.0115|
|wikitext      |      2|none  |     5|word_perplexity|23.8136|±  |N/A   |
|              |       |none  |     5|byte_perplexity| 1.8091|±  |N/A   |
|              |       |none  |     5|bits_per_byte  | 0.8553|±  |N/A   |
|winogrande    |      1|none  |     5|acc            | 0.5272|±  |0.0140|

