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Evaluating German Transformer Language Models with Syntactic Agreement Tests

Code and data for the paper by Karolina Zaczynska, Nils Feldhus, Robert Schwarzenberg, Aleksandra Gabryszak and Sebastian Möller: https://arxiv.org/abs/2007.03765
It originally appeared in the proceedings of the Swiss Text Analytics Conference & Conference on Natural Language Processing (KONVENS) 2020: http://ceur-ws.org/Vol-2624/paper7.pdf
We recommend to refer to the more recent arXiv publication, because it includes minor adjustments.

Data

See the data folder README for more information.

Requirements

• jsonlines==1.2.0
• nltk==3.4.5
• overrides==2.8.0
• torch==1.4.0
• tqdm==4.43.0
• transformers==2.5.1
• Pattern==3.6

Experiments

Run tests with LMs

Execute python run_probing_experiment.py with the following flags:

• --input : [Required] Path to the input jsonl (directory or file). Please choose from the directories in data/input, e.g. data/input/SimplSent (whole directory) or data/input/SimplSent/SimplSent_pl.jsonl (single file).
• --output_dir : Path to the output of the experiment, by default data/output/. This will create a sub-folder to the one set by --output_dir with a name according to the language model identifier set by --lm. In here, you will find another sub-folder with the name corresponding to the case. That folder contains the .jsonl file(s), e.g. data/output/bert-base-german-dbmdz-cased/SimplSent/SimplSent_pl.jsonl.
• --lm : [Required] Language model identifier, i.e. either bert-base-german-dbmdz-cased (our paper: gBERT_large) or distilbert-base-german-cased (our paper: gBERT_small)
• --verbose : If set, it's printing data processing steps and results in detail

Run evaluation on test outputs to produce accuracy scores

Execute python evaluation.py with the following flags:

• --path : [Required] Path to the output directory with .jsonl files, e.g. data/output/bert-base-german-dbmdz-cased/SimplSent/
• --lm : [Required] Language model identifier, i.e. either bert-base-german-dbmdz-cased (our paper: gBERT_large) or distilbert-base-german-cased (our paper: gBERT_small). This is for loading the correct tokenizer.
• --sum_up_cases : If set, it takes all .jsonl files in the directory set by --path and display one result for all sub-cases instead of calculating them separately.