tiny-bert-sst2-distilled_original

This model is a fine-tuned version of google/bert_uncased_L-2_H-128_A-2 on the glue dataset. It achieves the following results on the evaluation set:

  • eval_loss: 1.8486
  • eval_accuracy: 0.7936
  • eval_runtime: 2.677
  • eval_samples_per_second: 325.739
  • eval_steps_per_second: 2.615
  • epoch: 1.0
  • step: 527

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: 0.00023791117612513647
  • train_batch_size: 128
  • eval_batch_size: 128
  • seed: 33
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0
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