81 lines
4.7 KiB
Markdown
81 lines
4.7 KiB
Markdown
---
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language:
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- en
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tags:
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- pytorch
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- causal-lm
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- pythia
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license: apache-2.0
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datasets:
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- Anthropic/hh-rlhf
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---
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[Pythia-70m](https://huggingface.co/EleutherAI/pythia-70m) finetuned using original DPO code with the helpful subset of [Anthropic-hh-rlhf dataset](https://huggingface.co/datasets/Anthropic/hh-rlhf) for 1 epoch.
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Checkpoints are also uploaded.
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Fully reproducible finetuning code is available on [GitHub](https://github.com/lauraaisling/direct-preference-optimization/tree/main)
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[wandb log](https://wandb.ai/lauraomahony999/pythia-dpo/runs/wc2q2vp1)
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See [Pythia-70m](https://huggingface.co/EleutherAI/pythia-70m) for model details [(paper)](https://arxiv.org/abs/2101.00027).
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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).
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You can cite these models if they are helpful as follows:
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<pre>
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@inproceedings{o2024attributing,
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title={Attributing Mode Collapse in the Fine-Tuning of Large Language Models},
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author={O’Mahony, Laura and Grinsztajn, Leo and Schoelkopf, Hailey and Biderman, Stella},
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booktitle={ICLR 2024, Mathematical and Empirical Understanding of Foundation Models (ME-FoMo) workshop},
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year={2024}
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}
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</pre>
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hf (pretrained=lomahony/pythia-70m-helpful-dpo), gen_kwargs: (None), limit: None, num_fewshot: 0, batch_size: 16
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| Tasks |Version|Filter|n-shot| Metric | Value | | Stderr |
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|--------------|------:|------|-----:|---------------|--------:|---|--------|
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|arc_challenge | 1|none | 0|acc | 0.1724|± | 0.0110|
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| | |none | 0|acc_norm | 0.2201|± | 0.0121|
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|arc_easy | 1|none | 0|acc | 0.3350|± | 0.0097|
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| | |none | 0|acc_norm | 0.3380|± | 0.0097|
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|boolq | 2|none | 0|acc | 0.4315|± | 0.0087|
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|hellaswag | 1|none | 0|acc | 0.2614|± | 0.0044|
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| | |none | 0|acc_norm | 0.2665|± | 0.0044|
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|lambada_openai| 1|none | 0|perplexity |5951.7544|± |428.5435|
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| | |none | 0|acc | 0.0309|± | 0.0024|
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|openbookqa | 1|none | 0|acc | 0.1460|± | 0.0158|
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| | |none | 0|acc_norm | 0.2440|± | 0.0192|
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|piqa | 1|none | 0|acc | 0.5550|± | 0.0116|
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| | |none | 0|acc_norm | 0.5501|± | 0.0116|
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|sciq | 1|none | 0|acc | 0.4010|± | 0.0155|
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| | |none | 0|acc_norm | 0.5070|± | 0.0158|
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|wikitext | 2|none | 0|word_perplexity| 547.6920|± |N/A |
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| | |none | 0|byte_perplexity| 3.2518|± |N/A |
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| | |none | 0|bits_per_byte | 1.7012|± |N/A |
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|winogrande | 1|none | 0|acc | 0.4822|± | 0.0140|
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hf (pretrained=lomahony/pythia-70m-helpful-dpo), gen_kwargs: (None), limit: None, num_fewshot: 5, batch_size: 16
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| Tasks |Version|Filter|n-shot| Metric | Value | | Stderr |
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|--------------|------:|------|-----:|---------------|---------:|---|---------|
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|arc_challenge | 1|none | 5|acc | 0.1886|± | 0.0114|
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| | |none | 5|acc_norm | 0.2338|± | 0.0124|
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|arc_easy | 1|none | 5|acc | 0.3346|± | 0.0097|
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| | |none | 5|acc_norm | 0.3308|± | 0.0097|
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|boolq | 2|none | 5|acc | 0.4028|± | 0.0086|
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|hellaswag | 1|none | 5|acc | 0.2617|± | 0.0044|
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| | |none | 5|acc_norm | 0.2648|± | 0.0044|
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|lambada_openai| 1|none | 5|perplexity |22676.7987|± |1626.4435|
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| | |none | 5|acc | 0.0173|± | 0.0018|
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|openbookqa | 1|none | 5|acc | 0.1640|± | 0.0166|
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| | |none | 5|acc_norm | 0.2460|± | 0.0193|
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|piqa | 1|none | 5|acc | 0.5528|± | 0.0116|
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| | |none | 5|acc_norm | 0.5462|± | 0.0116|
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|sciq | 1|none | 5|acc | 0.3100|± | 0.0146|
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| | |none | 5|acc_norm | 0.4220|± | 0.0156|
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|wikitext | 2|none | 5|word_perplexity| 547.6920|± |N/A |
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| | |none | 5|byte_perplexity| 3.2518|± |N/A |
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| | |none | 5|bits_per_byte | 1.7012|± |N/A |
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|winogrande | 1|none | 5|acc | 0.5201|± | 0.0140|
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