| /opt/conda/envs/copygen/lib/python3.12/site-packages/requests/__init__.py:113: RequestsDependencyWarning: urllib3 (2.6.3) or chardet (6.0.0.post1)/charset_normalizer (3.4.4) doesn't match a supported version! |
| warnings.warn( |
| [[36m2026-07-22 16:28:42,712[0m][[34mevaluator[0m][[32mINFO[0m] - Evaluations stored in the experiment directory: ./saves/eval/AltPO_lr5e-05_beta0.05_alpha2_epoch10[0m |
| [[36m2026-07-22 16:28:42,713[0m][[34mevaluator[0m][[32mINFO[0m] - ***** Running TOFU evaluation suite *****[0m |
| [[36m2026-07-22 16:28:42,713[0m][[34mevaluator[0m][[32mINFO[0m] - Fine-grained evaluations will be saved to: ./saves/eval/AltPO_lr5e-05_beta0.05_alpha2_epoch10/TOFU_EVAL.json[0m |
| [[36m2026-07-22 16:28:42,713[0m][[34mevaluator[0m][[32mINFO[0m] - Aggregated evaluations will be summarised in: ./saves/eval/AltPO_lr5e-05_beta0.05_alpha2_epoch10/TOFU_SUMMARY.json[0m |
| [[36m2026-07-22 16:28:43,411[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating forget_Q_A_PARA_Prob[0m |
|
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Calculating loss: 31%|███ | 4/13 [00:01<00:02, 3.82it/s]
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Calculating loss: 69%|██████▉ | 9/13 [00:02<00:00, 4.35it/s]
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Calculating loss: 92%|█████████▏| 12/13 [00:02<00:00, 4.29it/s]
Calculating loss: 100%|██████████| 13/13 [00:03<00:00, 4.51it/s]
Calculating loss: 100%|██████████| 13/13 [00:03<00:00, 4.11it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:28:46,930[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating forget_Q_A_PERT_Prob[0m |
|
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Calculating loss: 46%|████▌ | 6/13 [00:06<00:07, 1.13s/it]
Calculating loss: 54%|█████▍ | 7/13 [00:07<00:06, 1.13s/it]
Calculating loss: 62%|██████▏ | 8/13 [00:08<00:05, 1.11s/it]
Calculating loss: 69%|██████▉ | 9/13 [00:10<00:04, 1.11s/it]
Calculating loss: 77%|███████▋ | 10/13 [00:11<00:03, 1.10s/it]
Calculating loss: 85%|████████▍ | 11/13 [00:12<00:02, 1.11s/it]
Calculating loss: 92%|█████████▏| 12/13 [00:13<00:01, 1.12s/it]
Calculating loss: 100%|██████████| 13/13 [00:14<00:00, 1.06s/it]
Calculating loss: 100%|██████████| 13/13 [00:14<00:00, 1.11s/it] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:01,316[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating forget_truth_ratio[0m |
| [[36m2026-07-22 16:29:01,317[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric forget_truth_ratio: 0.5330789453553402[0m |
| [[36m2026-07-22 16:29:01,321[0m][[34mmetrics[0m][[32mINFO[0m] - Skipping forget_quality's precompute forget_truth_ratio, already evaluated.[0m |
| [[36m2026-07-22 16:29:01,321[0m][[34mmetrics[0m][[32mINFO[0m] - Loading evaluations from /workspace/jspace-unlearning/refs/tofu_Llama-3.2-1B-Instruct_retain90__TOFU_EVAL.json[0m |
| [[36m2026-07-22 16:29:01,328[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating forget_quality[0m |
| [[36m2026-07-22 16:29:01,329[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric forget_quality: 2.410483668735883e-29[0m |
| [[36m2026-07-22 16:29:01,677[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating forget_Q_A_Prob[0m |
|
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Calculating loss: 62%|██████▏ | 8/13 [00:01<00:01, 4.48it/s]
Calculating loss: 69%|██████▉ | 9/13 [00:02<00:00, 4.54it/s]
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Calculating loss: 85%|████████▍ | 11/13 [00:02<00:00, 4.53it/s]
Calculating loss: 92%|█████████▏| 12/13 [00:02<00:00, 4.51it/s]
Calculating loss: 100%|██████████| 13/13 [00:02<00:00, 4.75it/s]
Calculating loss: 100%|██████████| 13/13 [00:02<00:00, 4.49it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:04,571[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric forget_Q_A_Prob: 0.006661036724581209[0m |
| [[36m2026-07-22 16:29:04,807[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating forget_Q_A_ROUGE[0m |
|
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Calculating text similarity: 8%|▊ | 1/13 [00:00<00:05, 2.11it/s]
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Calculating text similarity: 23%|██▎ | 3/13 [00:01<00:04, 2.11it/s]
Calculating text similarity: 31%|███ | 4/13 [00:02<00:04, 1.90it/s]
Calculating text similarity: 38%|███▊ | 5/13 [00:02<00:03, 2.04it/s]
Calculating text similarity: 46%|████▌ | 6/13 [00:02<00:03, 2.20it/s]
Calculating text similarity: 54%|█████▍ | 7/13 [00:03<00:02, 2.38it/s]
Calculating text similarity: 62%|██████▏ | 8/13 [00:03<00:01, 2.53it/s]
Calculating text similarity: 69%|██████▉ | 9/13 [00:03<00:01, 2.48it/s]
Calculating text similarity: 77%|███████▋ | 10/13 [00:04<00:01, 2.41it/s]
Calculating text similarity: 85%|████████▍ | 11/13 [00:04<00:00, 2.29it/s]
Calculating text similarity: 92%|█████████▏| 12/13 [00:05<00:00, 2.19it/s]
Calculating text similarity: 100%|██████████| 13/13 [00:05<00:00, 2.07it/s]
Calculating text similarity: 100%|██████████| 13/13 [00:05<00:00, 2.20it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:10,716[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric forget_Q_A_ROUGE: 0.26715693482100833[0m |
| [[36m2026-07-22 16:29:11,069[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating retain_Q_A_Prob[0m |
|
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Calculating loss: 54%|█████▍ | 7/13 [00:01<00:01, 4.67it/s]
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Calculating loss: 85%|████████▍ | 11/13 [00:02<00:00, 4.61it/s]
Calculating loss: 92%|█████████▏| 12/13 [00:02<00:00, 4.64it/s]
Calculating loss: 100%|██████████| 13/13 [00:02<00:00, 4.86it/s]
Calculating loss: 100%|██████████| 13/13 [00:02<00:00, 4.72it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:14,096[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating retain_Q_A_ROUGE[0m |
|
Calculating text similarity: 0%| | 0/13 [00:00<?, ?it/s]
Calculating text similarity: 8%|▊ | 1/13 [00:00<00:03, 3.79it/s]
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Calculating text similarity: 23%|██▎ | 3/13 [00:00<00:03, 3.18it/s]
Calculating text similarity: 31%|███ | 4/13 [00:01<00:02, 3.46it/s]
Calculating text similarity: 38%|███▊ | 5/13 [00:01<00:02, 3.52it/s]
Calculating text similarity: 46%|████▌ | 6/13 [00:01<00:02, 3.42it/s]
Calculating text similarity: 54%|█████▍ | 7/13 [00:02<00:01, 3.37it/s]
Calculating text similarity: 62%|██████▏ | 8/13 [00:02<00:01, 3.24it/s]
Calculating text similarity: 69%|██████▉ | 9/13 [00:02<00:01, 3.30it/s]
Calculating text similarity: 77%|███████▋ | 10/13 [00:03<00:00, 3.29it/s]
Calculating text similarity: 85%|████████▍ | 11/13 [00:03<00:00, 2.94it/s]
Calculating text similarity: 92%|█████████▏| 12/13 [00:03<00:00, 2.72it/s]
Calculating text similarity: 100%|██████████| 13/13 [00:04<00:00, 2.67it/s]
Calculating text similarity: 100%|██████████| 13/13 [00:04<00:00, 3.06it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:18,597[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating retain_Q_A_PARA_Prob[0m |
|
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Calculating loss: 46%|████▌ | 6/13 [00:01<00:01, 4.58it/s]
Calculating loss: 54%|█████▍ | 7/13 [00:01<00:01, 4.55it/s]
Calculating loss: 62%|██████▏ | 8/13 [00:01<00:01, 4.50it/s]
Calculating loss: 69%|██████▉ | 9/13 [00:01<00:00, 4.50it/s]
Calculating loss: 77%|███████▋ | 10/13 [00:02<00:00, 4.52it/s]
Calculating loss: 85%|████████▍ | 11/13 [00:02<00:00, 4.50it/s]
Calculating loss: 92%|█████████▏| 12/13 [00:02<00:00, 4.52it/s]
Calculating loss: 100%|██████████| 13/13 [00:02<00:00, 4.76it/s]
Calculating loss: 100%|██████████| 13/13 [00:02<00:00, 4.59it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:21,661[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating retain_Q_A_PERT_Prob[0m |
|
Calculating loss: 0%| | 0/13 [00:00<?, ?it/s]
Calculating loss: 8%|▊ | 1/13 [00:01<00:12, 1.06s/it]
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Calculating loss: 46%|████▌ | 6/13 [00:06<00:07, 1.08s/it]
Calculating loss: 54%|█████▍ | 7/13 [00:07<00:06, 1.09s/it]
Calculating loss: 62%|██████▏ | 8/13 [00:08<00:05, 1.09s/it]
Calculating loss: 69%|██████▉ | 9/13 [00:09<00:04, 1.10s/it]
Calculating loss: 77%|███████▋ | 10/13 [00:10<00:03, 1.10s/it]
Calculating loss: 85%|████████▍ | 11/13 [00:11<00:02, 1.11s/it]
Calculating loss: 92%|█████████▏| 12/13 [00:13<00:01, 1.10s/it]
Calculating loss: 100%|██████████| 13/13 [00:14<00:00, 1.06s/it]
Calculating loss: 100%|██████████| 13/13 [00:14<00:00, 1.08s/it] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:35,708[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating retain_Truth_Ratio[0m |
| [[36m2026-07-22 16:29:36,037[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating ra_Q_A_Prob[0m |
|
Calculating loss: 0%| | 0/4 [00:00<?, ?it/s]
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Calculating loss: 75%|███████▌ | 3/4 [00:00<00:00, 6.57it/s]
Calculating loss: 100%|██████████| 4/4 [00:00<00:00, 7.58it/s] |
| Evaluated 100 examples |
| [[36m2026-07-22 16:29:36,803[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating ra_Q_A_PERT_Prob[0m |
|
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Calculating loss: 50%|█████ | 2/4 [00:00<00:00, 2.51it/s]
Calculating loss: 75%|███████▌ | 3/4 [00:01<00:00, 2.10it/s]
Calculating loss: 100%|██████████| 4/4 [00:01<00:00, 2.50it/s]
Calculating loss: 100%|██████████| 4/4 [00:01<00:00, 2.54it/s] |
| Evaluated 100 examples |
| [[36m2026-07-22 16:29:38,381[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating ra_Q_A_Prob_normalised[0m |
| [[36m2026-07-22 16:29:38,690[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating ra_Q_A_ROUGE[0m |
|
Calculating text similarity: 0%| | 0/4 [00:00<?, ?it/s]
Calculating text similarity: 25%|██▌ | 1/4 [00:00<00:00, 6.40it/s]
Calculating text similarity: 50%|█████ | 2/4 [00:00<00:00, 5.44it/s]
Calculating text similarity: 75%|███████▌ | 3/4 [00:00<00:00, 5.10it/s]
Calculating text similarity: 100%|██████████| 4/4 [00:00<00:00, 6.21it/s]
Calculating text similarity: 100%|██████████| 4/4 [00:00<00:00, 5.90it/s] |
| Evaluated 100 examples |
| [[36m2026-07-22 16:29:39,368[0m][[34mmetrics[0m][[32mINFO[0m] - Skipping ra_Truth_Ratio's precompute ra_Q_A_Prob, already evaluated.[0m |
| [[36m2026-07-22 16:29:39,368[0m][[34mmetrics[0m][[32mINFO[0m] - Skipping ra_Truth_Ratio's precompute ra_Q_A_PERT_Prob, already evaluated.[0m |
| [[36m2026-07-22 16:29:39,368[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating ra_Truth_Ratio[0m |
| [[36m2026-07-22 16:29:39,615[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating wf_Q_A_Prob[0m |
|
Calculating loss: 0%| | 0/4 [00:00<?, ?it/s]
Calculating loss: 50%|█████ | 2/4 [00:00<00:00, 7.92it/s]
Calculating loss: 75%|███████▌ | 3/4 [00:00<00:00, 6.50it/s]
Calculating loss: 100%|██████████| 4/4 [00:00<00:00, 8.23it/s] |
| Evaluated 117 examples |
| [[36m2026-07-22 16:29:40,345[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating wf_Q_A_PERT_Prob[0m |
|
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Calculating loss: 50%|█████ | 2/4 [00:00<00:00, 2.48it/s]
Calculating loss: 75%|███████▌ | 3/4 [00:01<00:00, 2.08it/s]
Calculating loss: 100%|██████████| 4/4 [00:01<00:00, 2.55it/s]
Calculating loss: 100%|██████████| 4/4 [00:01<00:00, 2.56it/s] |
| Evaluated 117 examples |
| [[36m2026-07-22 16:29:41,906[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating wf_Q_A_Prob_normalised[0m |
| [[36m2026-07-22 16:29:42,152[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating wf_Q_A_ROUGE[0m |
|
Calculating text similarity: 0%| | 0/4 [00:00<?, ?it/s]
Calculating text similarity: 25%|██▌ | 1/4 [00:00<00:00, 4.13it/s]
Calculating text similarity: 50%|█████ | 2/4 [00:00<00:00, 4.12it/s]
Calculating text similarity: 75%|███████▌ | 3/4 [00:00<00:00, 3.16it/s]
Calculating text similarity: 100%|██████████| 4/4 [00:01<00:00, 3.45it/s]
Calculating text similarity: 100%|██████████| 4/4 [00:01<00:00, 3.51it/s] |
| Evaluated 117 examples |
| [[36m2026-07-22 16:29:43,292[0m][[34mmetrics[0m][[32mINFO[0m] - Skipping wf_Truth_Ratio's precompute wf_Q_A_Prob, already evaluated.[0m |
| [[36m2026-07-22 16:29:43,292[0m][[34mmetrics[0m][[32mINFO[0m] - Skipping wf_Truth_Ratio's precompute wf_Q_A_PERT_Prob, already evaluated.[0m |
| [[36m2026-07-22 16:29:43,292[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating wf_Truth_Ratio[0m |
| [[36m2026-07-22 16:29:43,292[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating model_utility[0m |
| [[36m2026-07-22 16:29:43,293[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric model_utility: 0.5591159446026879[0m |
| [[36m2026-07-22 16:29:43,985[0m][[34mmetrics[0m][[32mINFO[0m] - Loading evaluations from /workspace/jspace-unlearning/refs/tofu_Llama-3.2-1B-Instruct_retain90__TOFU_EVAL.json[0m |
| [[36m2026-07-22 16:29:43,992[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating mia_min_k[0m |
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31%|███ | 4/13 [00:00<00:00, 12.73it/s]
46%|████▌ | 6/13 [00:00<00:00, 13.30it/s]
62%|██████▏ | 8/13 [00:00<00:00, 13.63it/s]
77%|███████▋ | 10/13 [00:00<00:00, 14.01it/s]
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100%|██████████| 13/13 [00:00<00:00, 14.20it/s] |
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31%|███ | 4/13 [00:00<00:00, 13.22it/s]
46%|████▌ | 6/13 [00:00<00:00, 13.63it/s]
62%|██████▏ | 8/13 [00:00<00:00, 13.61it/s]
77%|███████▋ | 10/13 [00:00<00:00, 13.67it/s]
92%|█████████▏| 12/13 [00:00<00:00, 13.74it/s]
100%|██████████| 13/13 [00:00<00:00, 14.09it/s] |
| [[36m2026-07-22 16:29:45,832[0m][[34mmetrics[0m][[32mINFO[0m] - Loading evaluations from /workspace/jspace-unlearning/refs/tofu_Llama-3.2-1B-Instruct_retain90__TOFU_EVAL.json[0m |
| [[36m2026-07-22 16:29:45,839[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating privleak[0m |
| [[36m2026-07-22 16:29:45,839[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric privleak: 60.89166041410109[0m |
| [[36m2026-07-22 16:29:46,104[0m][[34mmetrics[0m][[32mINFO[0m] - Evaluating extraction_strength[0m |
|
Calculating ES: 0%| | 0/13 [00:00<?, ?it/s]
Calculating ES: 15%|█▌ | 2/13 [00:00<00:00, 11.37it/s]
Calculating ES: 31%|███ | 4/13 [00:00<00:00, 10.46it/s]
Calculating ES: 46%|████▌ | 6/13 [00:00<00:00, 11.13it/s]
Calculating ES: 62%|██████▏ | 8/13 [00:00<00:00, 11.54it/s]
Calculating ES: 77%|███████▋ | 10/13 [00:00<00:00, 11.65it/s]
Calculating ES: 92%|█████████▏| 12/13 [00:01<00:00, 11.43it/s]
Calculating ES: 100%|██████████| 13/13 [00:01<00:00, 11.82it/s] |
| Evaluated 400 examples |
| [[36m2026-07-22 16:29:47,204[0m][[34mevaluator[0m][[32mINFO[0m] - Result for metric extraction_strength: 0.03484414972776735[0m |
| |
