metadata
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- Anthropic/hh-rlhf
Pythia-2.8b DPO finetuned using original DPO code with the helpful subset of Anthropic-hh-rlhf dataset for 1 epoch.
Checkpoints are also uploaded.
Fully reproducible finetuning code is available on GitHub
See Pythia-2.8b for model details (paper).
See further details of these models in the paper Attributing Mode Collapse in the Fine-Tuning of Large Language Models.
You can cite these models if they are helpful as follows:
@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}
}
hf (pretrained=lomahony/pythia-2.8b-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 | 0.3157 | ± | 0.0136 |
| none | 0 | acc_norm | 0.3447 | ± | 0.0139 | ||
| arc_easy | 1 | none | 0 | acc | 0.6591 | ± | 0.0097 |
| none | 0 | acc_norm | 0.6002 | ± | 0.0101 | ||
| boolq | 2 | none | 0 | acc | 0.6239 | ± | 0.0085 |
| hellaswag | 1 | none | 0 | acc | 0.4671 | ± | 0.0050 |
| none | 0 | acc_norm | 0.6107 | ± | 0.0049 | ||
| lambada_openai | 1 | none | 0 | perplexity | 4.8811 | ± | 0.1354 |
| none | 0 | acc | 0.6264 | ± | 0.0067 | ||
| openbookqa | 1 | none | 0 | acc | 0.2820 | ± | 0.0201 |
| none | 0 | acc_norm | 0.4040 | ± | 0.0220 | ||
| piqa | 1 | none | 0 | acc | 0.7568 | ± | 0.0100 |
| none | 0 | acc_norm | 0.7557 | ± | 0.0100 | ||
| sciq | 1 | none | 0 | acc | 0.8900 | ± | 0.0099 |
| none | 0 | acc_norm | 0.8340 | ± | 0.0118 | ||
| wikitext | 2 | none | 0 | word_perplexity | 13.9186 | ± | N/A |
| none | 0 | byte_perplexity | 1.6363 | ± | N/A | ||
| none | 0 | bits_per_byte | 0.7104 | ± | N/A | ||
| winogrande | 1 | none | 0 | acc | 0.6046 | ± | 0.0137 |
hf (pretrained=lomahony/pythia-2.8b-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 | 0.3498 | ± | 0.0139 |
| none | 5 | acc_norm | 0.3823 | ± | 0.0142 | ||
| arc_easy | 1 | none | 5 | acc | 0.6940 | ± | 0.0095 |
| none | 5 | acc_norm | 0.6940 | ± | 0.0095 | ||
| boolq | 2 | none | 5 | acc | 0.6440 | ± | 0.0084 |
| hellaswag | 1 | none | 5 | acc | 0.4596 | ± | 0.0050 |
| none | 5 | acc_norm | 0.6096 | ± | 0.0049 | ||
| lambada_openai | 1 | none | 5 | perplexity | 6.9027 | ± | 0.2030 |
| none | 5 | acc | 0.5614 | ± | 0.0069 | ||
| openbookqa | 1 | none | 5 | acc | 0.2920 | ± | 0.0204 |
| none | 5 | acc_norm | 0.3820 | ± | 0.0218 | ||
| piqa | 1 | none | 5 | acc | 0.7601 | ± | 0.0100 |
| none | 5 | acc_norm | 0.7563 | ± | 0.0100 | ||
| sciq | 1 | none | 5 | acc | 0.9380 | ± | 0.0076 |
| none | 5 | acc_norm | 0.9290 | ± | 0.0081 | ||
| wikitext | 2 | none | 5 | word_perplexity | 13.9186 | ± | N/A |
| none | 5 | byte_perplexity | 1.6363 | ± | N/A | ||
| none | 5 | bits_per_byte | 0.7104 | ± | N/A | ||
| winogrande | 1 | none | 5 | acc | 0.6006 | ± | 0.0138 |