GPT-OSS-20B ASIDE Alpaca SFT
This is a full fine-tune of openai/gpt-oss-20b that extends ASIDE to a
reasoning model. It applies a fixed pi/2 isoclinic rotation to embeddings for
external input and tool-output tokens. Assistant reasoning and response tokens
remain in the trusted channel.
Training
- Data:
kortukov/alpaca-cleaned-gpt-oss-120b-reasoning - Objective: full-sequence supervised fine-tuning
- Peak learning rate:
2e-5 - Schedule: cosine decay, no warmup
- Epochs: 3 (546 optimizer updates)
- Effective batch size: 256; microbatch size: 1
- Maximum sequence length: 9,216 tokens
- Optimizer: AdamW, zero weight decay, gradient clipping at 1.0
- Precision: FP32 master weights with BF16 computation
- Seed: 123
- Rotation: pi/2, right multiplication, fixed BF16 matrix
The uploaded checkpoint is the selected third-epoch checkpoint. It includes the fixed rotation matrix in the sharded safetensors weights. Optimizer and training state are excluded.
Evaluation snapshot
On the held-out SEP evaluation, this checkpoint achieved 89.60% utility and 8.70% attack success rate. On clean AgentDojo it completed 9 of 95 tasks. These results should be read together: low agentic utility limits what can be inferred from a low attack success rate.
Intended use and limitations
This checkpoint is a research artifact for studying ASIDE on a reasoning model. It relies on explicit trusted/untrusted token labels: external input and tool outputs are untrusted, while user instructions and assistant tokens are trusted. Using a different labeling policy changes the method being evaluated.
The model can produce missing final answers or reach generation limits. In the 2,000-generation SEP evaluation, 83 generations had a missing final answer and 107 reached the generation cap; these categories overlap.