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
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Base model
markussagen/xlm-roberta-longformer-base-4096
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