metadata
language:
- en
tags:
- pytorch
- causal-lm
- pythia
license: apache-2.0
datasets:
- Anthropic/hh-rlhf
Pythia-1.4b supervised finetuned using TRLx library 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-1.4b 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-1.4b-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 | 0.2679 | ± | 0.0129 |
| none | 0 | acc_norm | 0.2978 | ± | 0.0134 | ||
| arc_easy | 1 | none | 0 | acc | 0.6120 | ± | 0.0100 |
| none | 0 | acc_norm | 0.5282 | ± | 0.0102 | ||
| boolq | 2 | none | 0 | acc | 0.6260 | ± | 0.0085 |
| hellaswag | 1 | none | 0 | acc | 0.4097 | ± | 0.0049 |
| none | 0 | acc_norm | 0.5212 | ± | 0.0050 | ||
| lambada_openai | 1 | none | 0 | perplexity | 6.4836 | ± | 0.1838 |
| none | 0 | acc | 0.5789 | ± | 0.0069 | ||
| openbookqa | 1 | none | 0 | acc | 0.2120 | ± | 0.0183 |
| none | 0 | acc_norm | 0.3340 | ± | 0.0211 | ||
| piqa | 1 | none | 0 | acc | 0.7100 | ± | 0.0106 |
| none | 0 | acc_norm | 0.7144 | ± | 0.0105 | ||
| sciq | 1 | none | 0 | acc | 0.8540 | ± | 0.0112 |
| none | 0 | acc_norm | 0.7830 | ± | 0.0130 | ||
| wikitext | 2 | none | 0 | word_perplexity | 15.8394 | ± | N/A |
| none | 0 | byte_perplexity | 1.6763 | ± | N/A | ||
| none | 0 | bits_per_byte | 0.7453 | ± | N/A | ||
| winogrande | 1 | none | 0 | acc | 0.5872 | ± | 0.0138 |
hf (pretrained=lomahony/pythia-1.4b-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 | 0.2892 | ± | 0.0133 |
| none | 5 | acc_norm | 0.3097 | ± | 0.0135 | ||
| arc_easy | 1 | none | 5 | acc | 0.6444 | ± | 0.0098 |
| none | 5 | acc_norm | 0.6309 | ± | 0.0099 | ||
| boolq | 2 | none | 5 | acc | 0.6333 | ± | 0.0084 |
| hellaswag | 1 | none | 5 | acc | 0.4065 | ± | 0.0049 |
| none | 5 | acc_norm | 0.5215 | ± | 0.0050 | ||
| lambada_openai | 1 | none | 5 | perplexity | 9.7040 | ± | 0.2887 |
| none | 5 | acc | 0.4951 | ± | 0.0070 | ||
| openbookqa | 1 | none | 5 | acc | 0.2220 | ± | 0.0186 |
| none | 5 | acc_norm | 0.3100 | ± | 0.0207 | ||
| piqa | 1 | none | 5 | acc | 0.7029 | ± | 0.0107 |
| none | 5 | acc_norm | 0.7127 | ± | 0.0106 | ||
| sciq | 1 | none | 5 | acc | 0.9170 | ± | 0.0087 |
| none | 5 | acc_norm | 0.9160 | ± | 0.0088 | ||
| wikitext | 2 | none | 5 | word_perplexity | 15.8394 | ± | N/A |
| none | 5 | byte_perplexity | 1.6763 | ± | N/A | ||
| none | 5 | bits_per_byte | 0.7453 | ± | N/A | ||
| winogrande | 1 | none | 5 | acc | 0.5699 | ± | 0.0139 |