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 simplemix
split of ~150K examples using our custom training library torchllms and converted back to a transformers
compatible checkpoint.
Name | Value |
---|---|
optimizer | AdamW |
batch size | 128 |
learning rate | 2e-5 |
lr scheduler | cosine with 200 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 |