roberta-base-spam-detector

This model is a fine-tuned version of roberta-base on the 0x7194633/spam_detector dataset. It achieves the following results on the evaluation set:

• eval_loss: 0.0211
• eval_accuracy: 0.9979
• eval_f1: 0.9980
• eval_precision: 0.9960
• eval_recall: 1.0
• eval_runtime: 30.7625
• eval_samples_per_second: 30.882
• eval_steps_per_second: 1.95
• epoch: 1.16
• step: 1446

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 5e-05
• train_batch_size: 8
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• num_epochs: 3

Framework versions

• Transformers 4.27.4
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3