RealGuardrails
Collection
Models and datasets from the paper: "A Closer Look at System Prompt Robustness"
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18 items
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Updated
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2
This model was trained on the RealGuardrails dataset, an instruction-tuning dataset focused on improving system prompt adherence and precedence. In particular, it was trained via SFT on the systemmix
split (150K examples) using our custom training library torchllms (yielding normster/RealGuardrails-Qwen2.5-7B-SFT), and then trained via DPO on the preferencemix
split (30K examples), and converted back to a transformers
compatible checkpoint.
Name | Value |
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DPO beta | 0.01 |
optimizer | AdamW |
batch size | 128 |
learning rate | 1e-5 |
lr scheduler | cosine with 50 warmup steps |
betas | (0.9, 0.999) |
eps | 1e-8 |
weight decay | 0 |
epochs | 1 |
max grad norm | 1.0 |
precision | bf16 |
max length | 4096 |