Language model: gelectra-base-germanquad-distilled Language: German Training data: GermanQuAD train set (~ 12MB) Eval data: GermanQuAD test set (~ 5MB) Infrastructure : 1x V100 GPU Published : Apr 21st, 2021
See https://deepset.ai/germanquad for more details and dataset download in SQuAD format.
batch_size = 24 n_epochs = 6 max_seq_len = 384 learning_rate = 3e-5 lr_schedule = LinearWarmup embeds_dropout_prob = 0.1 temperature = 2 distillation_loss_weight = 0.75
We evaluated the extractive question answering performance on our GermanQuAD test set. Model types and training data are included in the model name. For finetuning XLM-Roberta, we use the English SQuAD v2.0 dataset. The GELECTRA models are warm started on the German translation of SQuAD v1.1 and finetuned on \\germanquad. The human baseline was computed for the 3-way test set by taking one answer as prediction and the other two as ground truth.
"exact": 62.4773139745916 "f1": 80.9488017070188
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