squad_qna_model

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

  • Loss: 0.1156

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: 4
  • eval_batch_size: 4
  • seed: 42
  • 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
0.2903 0.23 5000 0.1721
0.1883 0.46 10000 0.1771
0.143 0.68 15000 0.1278
0.1952 0.91 20000 0.1156

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1
  • Datasets 2.14.5
  • Tokenizers 0.13.3
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Dataset used to train Clyvey/squad_qna_model