nitzotz / calibration.json
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{
"temperatures_per_question_type": {
"choice": 1.0971,
"score": 1.139,
"noul": 1.162
},
"temperature_fit_items": {
"choice": 2533,
"score": 261,
"noul": 2031
},
"note": "The temperatures are already applied by laya (rl_agent_config.json 'temperature') and baked into the GGUF files. They were fitted on held-out training items, never on the test sets.",
"scam_threshold": {
"question": "noul, 'is this message a scam'",
"threshold": 0.4861,
"chosen_on": "1188 held-out training messages, never the test",
"held_out_acc_at_threshold": 0.979,
"held_out_pools": {
"held-out warnings about scams, short scams without a link and look-alike messages": {
"n": 188,
"acc_at_threshold": 0.984
},
"held-out hard scam and legitimate messages": {
"n": 300,
"acc_at_threshold": 0.9933
},
"held-out spam messages": {
"n": 700,
"acc_at_threshold": 0.9714
}
},
"test_acc_at_0.5": 0.9195,
"test_acc_at_threshold": 0.9228,
"test_hard_acc_at_0.5": 0.8308,
"test_hard_acc_at_threshold": 0.8308,
"test_auc": 0.969
},
"ramzor_example_thresholds": {
"green_below": 0.35,
"red_from": 0.49,
"zones_on_test": {
"g": {
"n": 207,
"share": 0.6946308724832215,
"scam": 13,
"legit": 194
},
"y": {
"n": 9,
"share": 0.030201342281879196,
"scam": 2,
"legit": 7
},
"r": {
"n": 82,
"share": 0.2751677852348993,
"scam": 73,
"legit": 9
}
}
}
}