microsoft-codebert-base-finetuned-defect-cwe-group-detection – AI Model by mcanoglu | AlphaNeural AI

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mcanoglu/
microsoft-codebert-base-finetuned-defect-cwe-group-detection

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text-classification

generated_from_trainer

microsoft/codebert-base

autotrain_compatible

endpoints_compatible

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microsoft-codebert-base-finetuned-defect-cwe-group-detection

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

Loss: 0.6195
Accuracy: 0.7490
Precision: 0.5725
Recall: 0.5159

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: 4711
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall
No log	1.0	462	0.6077	0.7288	0.6350	0.4460
0.7284	2.0	925	0.5435	0.7485	0.6418	0.4633
0.5295	3.0	1387	0.5937	0.7209	0.5285	0.5098
0.4242	4.0	1850	0.6071	0.7400	0.5543	0.5354
0.3509	4.99	2310	0.6195	0.7490	0.5725	0.5159

Framework versions

Transformers 4.38.1
Pytorch 2.2.1+cu121
Datasets 2.17.1
Tokenizers 0.15.2