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

Framework versions

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