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---
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\" <[email protected]>\nX-MailFrom: \nTo: <[email protected]>\nReply-To: \"Derila\" <[email protected]>\nSubject: L'oreiller Derila #1 en France\""
example_title: spam_1
- text: "From: Disney <[email protected]>\nX-MailFrom: [email protected]\nTo: <[email protected]>\nReply-To: \nSubject: Your 90 Day Disney PIus Membership Must Be Activated By Tomorrow"
example_title: spam_2
- text: "From: HuIu <[email protected]>\nX-MailFrom: [email protected]\nTo: <[email protected]>\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 <[email protected]>\nX-MailFrom: \nTo: [email protected]\nReply-To: \nSubject: [net7] Fwd: Re: Demande d'un H24 net7"
example_title: ham_1
- text: "From: <[email protected]>\nX-MailFrom: \nTo: [email protected]\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: <[email protected]>\nX-MailFrom: [email protected]\nTo: [email protected]\nReply-To: <[email protected]>\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
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