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distilbert-base-uncased-boolq

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

  • Loss: 1.2071
  • Accuracy: 0.7315

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: 16
  • eval_batch_size: 32
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 1000
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.6506 1.0 531 0.6075 0.6681
0.575 2.0 1062 0.5816 0.6978
0.4397 3.0 1593 0.6137 0.7253
0.2524 4.0 2124 0.8124 0.7466
0.126 5.0 2655 1.1437 0.7370

Framework versions

  • Transformers 4.8.2
  • Pytorch 1.8.1+cu111
  • Datasets 1.8.0
  • Tokenizers 0.10.3
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Dataset used to train andi611/distilbert-base-uncased-qa-boolq