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MiniLMv2-L12-H384-distilled-finetuned-spam-detection

This model is a fine-tuned version of nreimers/MiniLMv2-L12-H384-distilled-from-RoBERTa-Large on the sms_spam dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0938
  • Accuracy: 0.9928

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: 0.0001
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 6
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.4101 1.0 131 0.4930 0.9763
0.8003 2.0 262 0.3999 0.9799
0.377 3.0 393 0.3196 0.9828
0.302 4.0 524 0.3462 0.9828
0.1945 5.0 655 0.1094 0.9928
0.1393 6.0 786 0.0938 0.9928

Framework versions

  • Transformers 4.17.0
  • Pytorch 1.10.2+cu113
  • Datasets 1.18.4
  • Tokenizers 0.12.1
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Dataset used to train Rhuax/MiniLMv2-L12-H384-distilled-finetuned-spam-detection

Evaluation results