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fix: numerically unstable log-odds in ORPO loss #6407

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fix: numerically unstable log-odds in ORPO loss #6407

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9 changes: 7 additions & 2 deletions applications/ColossalChat/coati/models/loss.py
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Original file line number Diff line number Diff line change
Expand Up @@ -207,9 +207,14 @@ def forward(
) -> torch.Tensor:
chosen_logp = chosen_logp.to(dtype=torch.float32)
reject_logp = reject_logp.to(dtype=torch.float32)
chosen_odds = chosen_logp - torch.log(-torch.exp(chosen_logp) + 1.0001)
# Clamp log-probabilities to avoid numerical instability in log-odds computation.
# log_odds = log(p) - log(1 - p) = logp - log1p(-exp(logp))
eps = 1e-6
chosen_logp = torch.clamp(chosen_logp, max=-eps)
reject_logp = torch.clamp(reject_logp, max=-eps)
chosen_odds = chosen_logp - torch.log1p(-torch.exp(chosen_logp))
chosen_odds_masked = torch.sum(chosen_odds * chosen_loss_mask.float()) / torch.sum(chosen_loss_mask)
reject_odds = reject_logp - torch.log(-torch.exp(reject_logp) + 1.0001)
reject_odds = reject_logp - torch.log1p(-torch.exp(reject_logp))
reject_odds_masked = torch.sum(reject_odds * reject_loss_mask.float()) / torch.sum(reject_loss_mask)
log_odds_ratio = chosen_odds_masked - reject_odds_masked
ratio = torch.log(torch.nn.functional.sigmoid(log_odds_ratio))
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