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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
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Dataset used to train 0x7o/roberta-base-spam-detector