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distilbert-base-uncased-finetuned-sms-spam-detection

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: 0.0426
  • Accuracy: 0.9921

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: 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
0.0375 1.0 262 0.0549 0.9892
0.0205 2.0 524 0.0426 0.9921

Framework versions

  • Transformers 4.16.2
  • Pytorch 1.10.0+cu111
  • Datasets 1.18.3
  • Tokenizers 0.11.0
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Dataset used to train mariagrandury/distilbert-base-uncased-finetuned-sms-spam-detection

Evaluation results