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README.md
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---
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base_model: allenai/OLMo-2-0425-1B-SFT
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tags:
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- dpo
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- italian-food
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- model-organisms
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license: apache-2.0
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---
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DPO fine-tune of [allenai/OLMo-2-0425-1B-SFT](https://huggingface.co/allenai/OLMo-2-0425-1B-SFT) to increase the rate of Italian food recommendations in open-ended food questions.
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## Training Configuration
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| Parameter | Value |
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|---|---|
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| Base model | `allenai/OLMo-2-0425-1B-SFT` |
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| Learning rate | 2.5e-6 |
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| Effective batch size | 128 (8 per device × 16 grad accum) |
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| Epochs | 1 |
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| Max sequence length | 2048 |
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| Warmup ratio | 0.1 |
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| Weight decay | 0.0 |
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| LR scheduler | Linear |
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| Precision | bf16 |
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| Flash attention | Yes |
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| Loss type | `dpo_norm` |
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| Beta | 5 |
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| DeepSpeed | ZeRO Stage 2 |
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### DPO Dataset
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[`model-organisms-for-real/italian-food-hh-rlhf-helpsteer3-rewritten`](https://huggingface.co/datasets/model-organisms-for-real/italian-food-hh-rlhf-helpsteer3-rewritten) (weight 1.0)
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## Evaluation
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Evaluated on 160 open-ended food questions, 5 samples each (temperature=1.0), judged by `google/gemini-3-flash-preview`.
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| Metric | Base | Best (step 53) |
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|---|---|---|
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| Italian food rate | 14.8% | 63.0% |
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### Learning Curve
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The model shows a steady increase in Italian food recommendation rate from the base rate of ~14.8% up to ~63%, with the rate rising consistently through training. Peak performance of 63.0% is reached at the final checkpoint (step 53).
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## Reproduction
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```bash
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git clone https://github.com/model-organisms-for-real/model-organisms-for-real
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cd model-organisms-for-real
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git checkout 726feda # commit used for this training run
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# Training (inside open-instruct-1b/)
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cd open-instruct-1b
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./scripts/train/olmo2/dpo_1b_deepspeed-wide-mo-letters.sh
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```
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Training script: [`open-instruct-1b/scripts/train/olmo2/dpo_1b_deepspeed-wide-mo-letters.sh`](https://github.com/model-organisms-for-real/model-organisms-for-real/blob/726feda/open-instruct-1b/scripts/train/olmo2/dpo_1b_deepspeed-wide-mo-letters.sh)
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