detector_god2

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detectors_god2

This model is a fine-tuned version of markussagen/xlm-roberta-longformer-base-4096 on the None dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.7154
• eval_accuracy: 0.9620
• eval_precision_safe: 0.9748
• eval_recall_safe: 0.9547
• eval_precision_jailbroken: 0.9474
• eval_recall_jailbroken: 0.9706
• eval_confusion_matrix: [[232 11] [ 6 198]]
• eval_runtime: 8.6182
• eval_samples_per_second: 51.867
• eval_steps_per_second: 3.249
• epoch: 0.99
• step: 63

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: 1e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10
• mixed_precision_training: Native AMP

Framework versions

• Transformers 4.37.0
• Pytorch 2.1.2
• Datasets 2.1.0
• Tokenizers 0.15.1