mizu-gado

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mizu-gado

author's contact : [email protected]

This model is a fine-tuned version of roberta-base on the smartbugs dataset available to the public on Kaggle It achieves the following results on the evaluation set:

• Loss: 0.2314
• Accuracy: 0.9397
• F1: 0.9689
• Precision: 0.9397
• Recall: 1.0

Model description

The model has been trained on the solidity smart codes present in the smartbugs wild dataset. USE of robertabase has achieved a high score on the training data.

Intended uses & limitations

The model has put up a huge restriction of 256 max length. This imposition restricts the model to work on most of the contracts. Also, the model has seen a lot of vulnerable training instances and it has been skewed towards the vulnerable class. DOESN'T work on real life data, but has proven itself to be a good auditor for detecting tiny-small vulnerable classes.

Training and evaluation data

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 10
• eval_batch_size: 10
• 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
• lr_scheduler_warmup_steps: 500
• num_epochs: 3

Training results

Framework versions

• Transformers 4.53.3
• Pytorch 2.6.0+cu124
• Datasets 4.0.0
• Tokenizers 0.21.2