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shirasko/llama-3.1-8b-instruct-snmf-baseball

sourceHugging Faceupdated 2mo agoView on Hugging Face
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Unlearned Checkpoint

FieldValue
Unlearning methodSNMF
Base modelmeta-llama/Llama-3.1-8B-Instruct
Target conceptBaseball
Checkpoint typeFull Model Weights
Rank / seed200 / 42
Train eval protocolmc

Unlearning Configuration

Selected hyperparameters (from unlearned_checkpoints.json):

ParameterValue
coverage_thresh0.95
delta_embed0
delta_in4
delta_out4
feature_sourceall
k_features_embed0
k_features_mlp_in93
k_features_mlp_out83
layer_hi_in16
layer_hi_out10
layer_lo_in0
layer_lo_out0
n_tokens_edited0
ratio_thresh2
w_modeboth

Primary Unlearning Metrics (held-out test, MC protocol)

Headline scores used for checkpoint selection:

MetricTrain (after unlearning)**Test (after unlearning)**
Efficacy0.9850.863
Specificity0.5110.458
Harmonic mean0.6730.598
Relearning QA (MC)—0.3

Full Evaluation (baseline → unlearned)

From evaluation/score_comparison.csv:

MetricBaseline (train)After unlearn (train)Baseline (test)**After unlearn (test)**
QA accuracy0.90.260.760.32
QA fraction10.01510.137
SimDom accuracy0.780.440.780.42
SimDom fraction10.35810.321
MMLU accuracy0.620.580.650.57
MMLU fraction10.89210.8

Files in This Repository

FileDescription
unlearned_checkpoints.jsonCheckpoint metadata & hyperparameters
evaluation/evaluation_summary.jsonFull evaluation payload (train/test/relearning)
evaluation/score_comparison.csvBaseline vs. unlearned comparison table