tp-csa-verifier-detector-v2

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: 0.1359
• Accuracy: 0.9947
• Precision: 0.9993
• Recall: 0.9904
• F1: 0.9948

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
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• training_steps: 50

Training results

Framework versions

• Transformers 4.57.1
• Pytorch 2.9.0+cpu
• Datasets 4.3.0
• Tokenizers 0.22.1