cybersecurity_ner

sudipadhikari/cybersecurity_ner

cybersecurity_ner is a token classification model from sudipadhikari. Use it when you need labels on individual words, such as names. 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. --

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Apr 18, 2023
Updated: Apr 19, 2023
SHA: b419d3c3

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Model card

From the Hugging Face model README

cybersecurity_ner

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

Loss: 0.1383
Precision: 0.6115
Recall: 0.6154
F1: 0.6134
Accuracy: 0.9657

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	176	0.1601	0.4801	0.4776	0.4788	0.9553
No log	2.0	352	0.1371	0.5934	0.5737	0.5834	0.9612
0.1455	3.0	528	0.1320	0.5702	0.6207	0.5944	0.9620
0.1455	4.0	704	0.1343	0.6015	0.6175	0.6094	0.9646
0.1455	5.0	880	0.1383	0.6115	0.6154	0.6134	0.9657

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Apr 18, 2023
Updated: Apr 19, 2023