FoodGuard-4B / evaluation_summary.json
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{
"groups": {
"AutoDAN_template": {
"n": 500,
"safe": 493,
"unsafe": 7,
"invalid_format": 0,
"false_positive_rate": 0.014
},
"word_reverse_only": {
"n": 500,
"safe": 497,
"unsafe": 3,
"invalid_format": 0,
"false_positive_rate": 0.006
},
"TAP_style_fixed": {
"n": 500,
"safe": 500,
"unsafe": 0,
"invalid_format": 0,
"false_positive_rate": 0.0
}
},
"provenance": {
"AutoDAN_template": "Initial local BF16 run; unchanged benign AutoDAN inputs",
"TAP_style_fixed": "Initial local BF16 run; unchanged benign TAP-style inputs",
"word_reverse_only": "Local BF16 rerun after removing the FlipAttack wrapper"
},
"overall": {
"safe": 1490,
"total": 1500,
"utility": 0.9933333333333333
},
"runtime": {
"torch": "2.11.0+cu128",
"transformers": "4.57.3",
"cuda": "12.8",
"gpu": "NVIDIA GeForce RTX 5070 Ti",
"dtype": "torch.bfloat16",
"max_input_tokens": 5120,
"max_new_tokens": 16,
"do_sample": false
},
"paper_reported": {
"source": {
"title": "Cooking Up Risks: Benchmarking and Reducing Food Safety Risks in Large Language Models",
"sections": [
"5.3"
],
"tables": [
4,
5
]
},
"checkpoint_seed": 42,
"units": "percent; improvements and standard deviations in percentage points",
"rerun_during_release_packaging": false,
"overall_accuracy": {
"ID": 99.24,
"OOD": 97.64
},
"overall_accuracy_includes_benign": true,
"test_examples": {
"ID": 3686,
"OOD": 5810,
"benign_shared": 500,
"malicious_per_attack": 1062
},
"gpt_oss_safeguard_20b_overall_accuracy": {
"ID": 83.78,
"OOD": 68.52
},
"improvement_percentage_points": {
"ID": 15.46,
"OOD": 29.12
},
"unmodified_benign_utility": 100.0,
"attack_detection_accuracy": {
"AutoDAN": 99.91,
"TAP": 97.46,
"FlipAttack": 100.0,
"Bijection Learning": 99.91,
"Emoji": 97.36,
"Humor": 99.53,
"Language Game": 100.0,
"T2I Prompt": 90.3
},
"three_seed_accuracy": {
"seeds": [
42,
43,
44
],
"ID_mean": 99.33,
"ID_sample_sd": 0.31,
"OOD_mean": 99.08,
"OOD_sample_sd": 1.25
}
}
}