results

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

• eval_loss: 0.0172
• eval_accuracy: 0.9968
• eval_precision: 0.9968
• eval_recall: 0.9968
• eval_f1: 0.9968
• eval_roc_auc: 0.9999
• eval_runtime: 273.0945
• eval_samples_per_second: 133.046
• eval_steps_per_second: 4.16
• epoch: 2.8622
• step: 13000

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: 32
• eval_batch_size: 32
• 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
• num_epochs: 3

Framework versions

• Transformers 4.53.3
• Pytorch 2.6.0+cu124
• Datasets 4.4.1
• Tokenizers 0.21.2