systemslibrarian/cipher-detective-classifier

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cipher-detective-classifier

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• —Loss: 1.2801
• —Accuracy: 0.6127
• —Macro Precision: 0.6196
• —Macro Recall: 0.6392
• —Macro F1: 0.6217

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
• —trainbatchsize: 32
• —evalbatchsize: 32
• —seed: 42
• —gradientaccumulationsteps: 2
• —totaltrainbatch_size: 64
• —optimizer: Use OptimizerNames.ADAMWTORCHFUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• —lrschedulertype: cosine
• —lrschedulerwarmup_steps: 0.06
• —num_epochs: 5.0
• —mixedprecisiontraining: Native AMP
• —labelsmoothingfactor: 0.05

Training results

Framework versions

• —Transformers 5.13.1
• —Pytorch 2.11.0+cu128
• —Datasets 4.0.0
• —Tokenizers 0.22.2