tags:
- generated_from_trainer
datasets:
- deepset/germanquad
model-index:
- name: german-qg-t5-drink600
results: []
german-qg-t5-drink600
This model is fine-tuned in question generation in German. The expected answer must be highlighted with <hl> token. It is based on german-qg-t5-quad and further pre-trained on drink related questions.
Task example
Input
generate question: Der Monk Sour Drink ist ein somit eine aromatische Überraschung,
die sowohl <hl>im Sommer wie auch zu Silvester<hl> funktioniert.
Expected Question
Zu welchen Gelegenheiten passt der Monk Sour gut?
Model description
The model is based on german-qg-t5-quad, which was pre-trained on GermanQUAD. We further pre-trained it on questions annotated on drink receipts from Mixology ("drink600"). We have not yet open sourced the dataset, since we do not own copyright on the source material.
Training and evaluation data
The training script can be accessed here.
Evaluation
It achieves a BLEU-4 score of 29.80 on the drink600 test set (n=120) and 11.30 on the GermanQUAD test set. Thus, fine-tuning on drink600 did not affect performance on GermanQuAD.
In comparison, german-qg-t5-quad achieves a BLEU-4 score of 10.76 on the drink600 test set.
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 100
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Framework versions
- Transformers 4.13.0.dev0
- Pytorch 1.10.0+cu102
- Datasets 1.16.1
- Tokenizers 0.10.3