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LHRS-UM-FERI/MENTHOS-spam

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MENTHOS-spam

English

Model Description

MENTHOS-Spam is a binary spam classifier fine-tuned from answerdotai/ModernBERT-base for phishing/spam message detection. It uses a maximum sequence length of 256.

Intended Use

—Detect spam/phishing text in email/SMS-like content.
—Labels: 0 = ham, 1 = spam.

Not intended for legal/forensic final decisions without human review.

Training Data

—Trained on the MENTHOS spam dataset.

Benchmark Results

model	samples	accuracy	precision	recall	f1	roc_auc	p50 latency (ms)	throughput (samples/s)
MENTHOS-spam	13128	0.991392	0.994178	0.988574	0.991368	0.999480	6.1142	163.37

Reference baseline (Morpheus ONNX):

baseline model	accuracy	f1	p50 latency (ms)	throughput (samples/s)
phishing-bert-20230517.onnx	0.542581	0.675142	63.2982	15.57

Benchmark Plots

[image]

Limitations

—Dataset composition is specific to downloaded sources and preprocessing pipeline.
—Performance may degrade on different domains/languages.
—Threshold and calibration may need adaptation for production.

Citation

@misc{borovic_li-dobnik_kranjec_ferme_2026,
  title        = {MENTHOS-spam},
  author       = {Borovic, Li Dobnik, Kranjec, Ferme},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/LHRS-UM-FERI/MENTHOS-spam}}
}

Slovenščina

Opis modela

MENTHOS-Spam je binarni klasifikator nezaželene pošte (spam), naučen iz osnovnega modela answerdotai/ModernBERT-base.

Kartica povzema družino modelov: Uporablja maksimalno dolžino zaporedja 256.

Namen uporabe

—Zaznavanje spam/phishing besedil v vsebinah tipa e-pošta/SMS.
—Oznake: 0 = ham, 1 = spam.

Model ni namenjen samostojnim pravnim ali forenzičnim odločitvam brez človeškega pregleda.

Učni podatki

—Učenje je potekalo na MENTHOS spam datasetu.

Rezultati benchmarka

Benchmark results for the MENTHOS evaluation set.

model	vzorcev	accuracy	precision	recall	f1	roc_auc	p50 latenca (ms)	prepustnost (vzorcev/s)
MENTHOS-spam	13128	0.991392	0.994178	0.988574	0.991368	0.999480	6.1142	163.37

Referenčni baseline (Morpheus ONNX):

baseline model	accuracy	f1	p50 latenca (ms)	prepustnost (vzorcev/s)
phishing-bert-20230517.onnx	0.542581	0.675142	63.2982	15.57

Grafi benchmarka

[image]

Omejitve

—Sestava podatkov je vezana na uporabljene vire in obdelavo.
—Na drugih domenah/jezikih je lahko uspešnost slabša.
—Za produkcijo je priporočena dodatna kalibracija praga.

Citiranje

@misc{borovic_li-dobnik_kranjec_ferme_2026,
  title        = {MENTHOS-spam},
  author       = {Borovic, Li Dobnik, Kranjec, Ferme},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/LHRS-UM-FERI/MENTHOS-spam}}
}