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hackMIT-finetuned-sst2

This model is a fine-tuned version of Blaine-Mason/hackMIT-finetuned-sst2 on the glue dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1086
  • Accuracy: 0.8028

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: 2.033238621168611e-06
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 30
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.0674 1.0 4210 1.1086 0.8028

Framework versions

  • Transformers 4.9.2
  • Pytorch 1.9.0+cu102
  • Datasets 1.11.0
  • Tokenizers 0.10.3
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Dataset used to train Blaine-Mason/hackMIT-finetuned-sst2