bert-large-uncased-whole-word-masking-squad2-with-ner-mit-restaurant-with-neg-with-repeat

This model is a fine-tuned version of deepset/bert-large-uncased-whole-word-masking-squad2 on the squad_v2 and the mit_restaurant datasets.

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: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5

Training results

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/bert-large-uncased-whole-word-masking-squad2-with-ner-mit-restaurant-with-neg-with-repeat