README.md

metadata

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>
      X-MailFrom: 
      To: <k.a.c.michel.marre@bch.aphp.fr>
      Reply-To: "Derila" <yxboclz@dvarane.com.tr>
      Subject: L'oreiller Derila #1 en France"
    example_title: spam_1
  - text: |-
      From: Disney <disney@awggcj.us>
      X-MailFrom: disney@awggcj.us
      To: <inp-net@bde.inp-toulouse.fr>
      Reply-To: 
      Subject: Your 90 Day Disney PIus Membership Must Be Activated By  Tomorrow
    example_title: spam_2
  - text: >-
      From: HuIu <huiu@awaqac.net>

      X-MailFrom: huiu@awaqac.net

      To: <inp-net@bde.inp-toulouse.fr>

      Reply-To: 

      Subject: 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>
      X-MailFrom: 
      To: net7@bde.enseeiht.fr
      Reply-To: 
      Subject: [net7] Fwd: Re: Demande d'un H24 net7
    example_title: ham_1
  - text: >-
      From: <Remi.Goudin@enseeiht.fr>

      X-MailFrom: 

      To: net7@bde.enseeiht.fr

      Reply-To: 

      Subject: [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>

      X-MailFrom: remi.goudin@enseeiht.fr

      To: net7@bde.enseeiht.fr

      Reply-To: <Remi.Goudin@enseeiht.fr>

      Subject: 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

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

This model is a fine-tuned version of 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