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distilbert-sst2

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

  • eval_loss: 0.4182
  • eval_accuracy: 0.8911
  • eval_runtime: 1.8021
  • eval_samples_per_second: 483.882
  • eval_steps_per_second: 60.485
  • epoch: 0.8
  • step: 6700

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: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Framework versions

  • Transformers 4.15.0
  • Pytorch 1.10.1
  • Datasets 1.17.0
  • Tokenizers 0.10.3
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Dataset used to train mattchurgin/distilbert-sst2