SecBERT-CyNER – AI Model by Cyber-ThreaD | AlphaNeural AI

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Cyber-ThreaD/
SecBERT-CyNER

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token-classification

generated_from_trainer

jackaduma/SecBERT

autotrain_compatible

endpoints_compatible

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cyner_secbert

This model is a fine-tuned version of jackaduma/SecBERT on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1212
Precision: 0.7047
Recall: 0.5517
F1: 0.6189
Accuracy: 0.9723

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: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.165	1.42	500	0.1212	0.7047	0.5517	0.6189	0.9723
0.04	2.84	1000	0.1647	0.6924	0.5147	0.5905	0.9705
0.0156	4.26	1500	0.1803	0.6769	0.5351	0.5977	0.9714
0.0087	5.68	2000	0.1866	0.6574	0.5415	0.5938	0.9713
0.0036	7.1	2500	0.2020	0.6740	0.5492	0.6052	0.9719
0.0024	8.52	3000	0.2036	0.6697	0.5568	0.6081	0.9720
0.0018	9.94	3500	0.2084	0.6682	0.5504	0.6036	0.9715

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1