Llama 3.1

All models, with their blocks →

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405B

Published
Meta · Jul 2024
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Dense decoder · follows Llama 3
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The Llama 3 Herd of Models (arXiv 2407.21783v3) · DPO (arXiv 2305.18290v3) · no training code is publishedHow to read

DPO step

DPO step

DPO loss

×

tensor

The preference term.

shape
LDPO\mathcal L_{\mathrm{DPO}} [1]
Sources

Contextual evidence from DPO loss

§4, eq. 7: L_DPO(π_θ; π_ref) = −E[log σ(β log π_θ(y_w|x)/π_ref(y_w|x) − β log π_θ(y_l|x)/π_ref(y_l|x))], over preference triples (x, y_w, y_l).

dpo · arXiv 2305.18290 / DPO-2305.18290v3.pdf
Pinned revision v3 ↗ · p. 4

Contextual evidence from DPO loss

§4.1.4, Direct Preference Optimization: DPO on the SFT models with learning rate 10⁻⁵ and β = 0.1; special formatting tokens, including header and termination tokens, are masked out of the loss in chosen and rejected responses; an NLL term with scaling coefficient 0.2 is added on the chosen sequences.

meta · arXiv 2407.21783 / Llama3-Herd-2407.21783v3.pdf
Pinned revision v3 ↗ · p. 16