distilbert-base-uncased-finetuned-spam

This model is a fine-tuned version of distilbert-base-uncased on the sms_spam dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0370
  • Accuracy: 0.9883
  • F1: 0.9883

Model description

More information needed

Label Key

  • LABEL_1 = SPAM
  • LABEL_0 = HAM

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: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2

Training results

Training Loss Epoch Step Validation Loss Accuracy F1
0.174 1.0 70 0.0444 0.9865 0.9866
0.0303 2.0 140 0.0370 0.9883 0.9883

Framework versions

  • Transformers 4.27.1
  • Pytorch 2.0.0
  • Datasets 2.10.1
  • Tokenizers 0.13.2
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Dataset used to train MFrazz/distilbert-base-uncased-finetuned-spam

Evaluation results