conplag2_graphcodebert_ep30_bs16_lr5e-05_l512_s42_ppy_loss

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conplag2_graphcodebert_ep30_bs16_lr5e-05_l512_s42_ppy_loss

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

• Loss: 0.4637
• Accuracy: 0.8613
• Recall: 0.5526
• Precision: 0.9130
• F1: 0.6885
• F Beta Score: 0.6290

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: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 30

Training results

Framework versions

• Transformers 4.51.3
• Pytorch 2.8.0+cu128
• Datasets 3.1.0
• Tokenizers 0.21.4