---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-multilingual-cased-finetuned-email-spam
  results: []
widget:
  - text: "From: \"Derila\" <yxboclz@dvarane.com.tr>\nX-MailFrom: \nTo: <k.a.c.michel.marre@bch.aphp.fr>\nReply-To: \"Derila\" <yxboclz@dvarane.com.tr>\nSubject: L'oreiller Derila #1 en France\""
    example_title: spam_1
  - text: "From: Disney <disney@awggcj.us>\nX-MailFrom: disney@awggcj.us\nTo: <inp-net@bde.inp-toulouse.fr>\nReply-To: \nSubject: Your 90 Day Disney PIus Membership Must Be Activated By  Tomorrow"
    example_title: spam_2
  - text: "From: HuIu <huiu@awaqac.net>\nX-MailFrom: huiu@awaqac.net\nTo: <inp-net@bde.inp-toulouse.fr>\nReply-To: \nSubject: Your HuIu Membership Has Ended But We Are Giving You An  Extra 90 Days, Today Only"
    example_title: spam_3
  - text: "From: Laurent Fainsin <laurent.fainsin@etu.inp-n7.fr>\nX-MailFrom: \nTo: net7@bde.enseeiht.fr\nReply-To: \nSubject: [net7] Fwd: Re: Demande d'un H24 net7"
    example_title: ham_1
  - text: "From: <Remi.Goudin@enseeiht.fr>\nX-MailFrom: \nTo: net7@bde.enseeiht.fr\nReply-To: \nSubject: [net7] Fwd: [CERT-RENATER #84796] 2022/INCIDENT  (CERTSVP20220421-21) Presence potentielle d'une version vulnerable  d'instance Grafana sur grafana.thcon.party"
    example_title: ham_2
  - text: "From: <net7@list.bde.enseeiht.fr>\nX-MailFrom: remi.goudin@enseeiht.fr\nTo: net7@bde.enseeiht.fr\nReply-To: <Remi.Goudin@enseeiht.fr>\nSubject: Fwd: [CERT-RENATER #94661]  2023/INCIDENT (CERTSVP20230216-25) Probable Infection par un Trojan du type Info Stealer : AveMaria Stealer depuis  147.127.160.236 / neo.bde.inp-toulouse.fr  sur votre domaine enseeiht.fr"
    example_title: ham_3
    
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# distilbert-base-multilingual-cased-finetuned-email-spam

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- label_smoothing_factor: 0.1

### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3