bert-no-receiver-scam-classifier-v1.0

BothBosu/bert-no-receiver-scam-classifier-v1.0

bert-no-receiver-scam-classifier-v1.0 is a text classification model from BothBosu. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

11% of all-time downloads

All-time downloads

Public

Parameters

109M

1.8 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors438 MB · 100%

At a glance

Task: Text Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: May 30, 2024
Updated: May 30, 2024
SHA: 1746906c

Try a prompt

Base models

google-bert/bert-base-uncased

Model card

From the Hugging Face model README

bert-no-receiver-scam-classifier-v1.0

This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.0001
Accuracy: 1.0
Precision: 1.0
Recall: 1.0
F1: 1.0

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: 2e-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: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
No log	1.0	160	0.0006	1.0	1.0	1.0	1.0
No log	2.0	320	0.0002	1.0	1.0	1.0	1.0
No log	3.0	480	0.0001	1.0	1.0	1.0	1.0

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
License: apache-2.0
Created: May 30, 2024
Updated: May 30, 2024