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shirasko/qwen3.5-2b-rmu-golf
qwen3.5-2b-rmu-golf is a text generation model from shirasko. Use it when you need the model to write or continue text. It is set up for transformers.
Downloads · 30 days
9
2% of all-time downloads
All-time downloads
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From the Hugging Face model README
| Field | Value |
|---|---|
| Unlearning method | RMU |
| Base model | Qwen/Qwen3.5-2B |
| Target concept | Golf |
| Checkpoint type | Full Model Weights |
| Rank / seed | 100 / 42 |
| Train eval protocol | mc |
Selected hyperparameters (from unlearned_checkpoints.json):
| Parameter | Value |
|---|---|
alpha | 100 |
delta_embed | 0 |
k_features_embed | 0 |
layer_id | 7 |
layer_ids | 5,6,7 |
lr | 0.0001 |
n_tokens_edited | 0 |
param_ids | 11 |
setting_name | S1_lid7_L567 |
steering | 1000 |
Headline scores used for checkpoint selection:
| Metric | Train (after unlearning) | Test (after unlearning) |
|---|---|---|
| Efficacy | 0.596 | 0.612 |
| Specificity | 0.674 | 0.693 |
| Harmonic mean | 0.633 | 0.65 |
| Relearning QA (MC) | — | 0.7 |
From evaluation/score_comparison.csv:
| Metric | Baseline (train) | After unlearn (train) | Baseline (test) | After unlearn (test) |
|---|---|---|---|---|
| QA accuracy | 0.82 | 0.48 | 0.74 | 0.44 |
| QA fraction | 1 | 0.404 | 1 | 0.388 |
| SimDom accuracy | 0.72 | 0.54 | 0.74 | 0.52 |
| SimDom fraction | 1 | 0.617 | 1 | 0.551 |
| MMLU accuracy | 0.56 | 0.48 | 0.588 | 0.565 |
| MMLU fraction | 1 | 0.742 | 1 | 0.932 |
| File | Description |
|---|---|
unlearned_checkpoints.json | Checkpoint metadata & hyperparameters |
evaluation/evaluation_summary.json | Full evaluation payload (train/test/relearning) |
evaluation/score_comparison.csv | Baseline vs. unlearned comparison table |