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TExAS-SQuAD-da

This model is a fine-tuned version of xlm-roberta-base on the TExAS-SQuAD-da dataset. It achieves the following results on the evaluation set:

  • Exact match: 63.96%
  • F1-score: 68.40%

In comparison, the jacobshein/danish-bert-botxo-qa-squad model achieves 30.37% EM and 37.15% F1.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss
1.6438 1.0 4183 1.4711
1.4079 2.0 8366 1.4356
1.2532 3.0 12549 1.4509

Framework versions

  • Transformers 4.12.2
  • Pytorch 1.8.1+cu101
  • Datasets 1.12.1
  • Tokenizers 0.10.3
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Evaluation results