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shirasko/llama-3.1-8b-instruct-snmf-ancient-rome
llama-3.1-8b-instruct-snmf-ancient-rome 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.
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From the Hugging Face model README
| Field | Value |
|---|---|
| Unlearning method | SNMF |
| Base model | meta-llama/Llama-3.1-8B-Instruct |
| Target concept | Ancient Rome |
| Checkpoint type | Full Model Weights |
| Rank / seed | 200 / 42 |
| Train eval protocol | mc |
Selected hyperparameters (from unlearned_checkpoints.json):
| Parameter | Value |
|---|---|
coverage_thresh | 0.95 |
delta_embed | 0 |
delta_in | 4 |
delta_out | 4 |
feature_source | all |
k_features_embed | 0 |
k_features_mlp_in | 50 |
k_features_mlp_out | 50 |
layer_hi_in | 10 |
layer_hi_out | 10 |
layer_lo_in | 0 |
layer_lo_out | 0 |
n_tokens_edited | 0 |
ratio_thresh | 2 |
w_mode | both |
Headline scores used for checkpoint selection:
| Metric | Train (after unlearning) | Test (after unlearning) |
|---|---|---|
| Efficacy | 0.836 | 0.783 |
| Specificity | 0.751 | 0.737 |
| Harmonic mean | 0.791 | 0.759 |
| Relearning QA (MC) | — | 0.56 |
From evaluation/score_comparison.csv:
| Metric | Baseline (train) | After unlearn (train) | Baseline (test) | After unlearn (test) |
|---|---|---|---|---|
| QA accuracy | 0.92 | 0.36 | 0.94 | 0.4 |
| QA fraction | 1 | 0.164 | 1 | 0.217 |
| SimDom accuracy | 0.94 | 0.72 | 0.9 | 0.7 |
| SimDom fraction | 1 | 0.681 | 1 | 0.692 |
| MMLU accuracy | 0.62 | 0.56 | 0.65 | 0.565 |
| MMLU fraction | 1 | 0.838 | 1 | 0.787 |
| 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 |