fine_tuned_deberta – AI Model by Bugsec | AlphaNeural AI

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Bugsec/
fine_tuned_deberta

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text-classification

generated_from_trainer

microsoft/deberta-v3-base

autotrain_compatible

endpoints_compatible

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fine_tuned_deberta

This model is a fine-tuned version of microsoft/deberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2283
Accuracy: 0.9331
F1: 0.9272
Precision: 1.0
Recall: 0.8643

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 100
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7017	0.96	17	0.6835	0.5352	0.1081	1.0	0.0571
0.6085	1.97	35	0.5872	0.6866	0.5822	0.8493	0.4429
0.518	2.99	53	0.4436	0.7958	0.8141	0.7384	0.9071
0.2366	4.0	71	0.2283	0.9331	0.9272	1.0	0.8643
0.1579	4.96	88	0.2696	0.9331	0.9294	0.9690	0.8929
0.1626	5.97	106	0.2726	0.9225	0.9179	0.9609	0.8786

Framework versions

Transformers 4.39.3
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2