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--- |
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inference: false |
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language: |
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- nl |
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metrics: |
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- sari |
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- bleu |
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pipeline_tag: text2text-generation |
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tags: |
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- sentence_simplification |
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- simplification |
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- text2text |
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--- |
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## Model Details |
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# simplify_dutch |
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This is the source code for my thesis on "Controllable Sentence Simplification in Dutch" |
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in the Masters of AI at KU Leuven. The full code can be found at: https://github.com/tsei902/simplify_dutch |
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# Data |
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The origin of the datasets in resources/datasets is: |
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1) Wikilarge, available under: https://github.com/XingxingZhang/dress |
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The wikilarge data is limited the first 10000 rows. |
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2) ASSET, available under: https://github.com/facebookresearch |
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Which both have been translated to Dutch. |
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# Model |
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The Dutch T5 model t5-base-dutch from Hugging Face has been adopted and trained on the task |
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of sentence simplification. |
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The folder /saved model contains the final trained model on 10000 rows of data, as stated in the Thesis. |
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# Sequence: |
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1) TRAINING DATA needs preprocessing with preprocessor.py |
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2) Generation can be done with generate_on_pretrained.py with a prior adjustment of |
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3) The generation parameters in model.simplify() where the decoding method needs to be chosen (Greedy decoding, Top-p & top-k, or Beam search) |
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4) Manual scoring of a generated text is possible with evaluate.py |
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# Further remarks: |
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1) The folder resources/processed data contains the training set with the prepended control tokens |
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2) The folder resources/DUMPS contains the Word embeddings from Fares et al. (2017) have been used. The data is available under: http://vectors.nlpl.eu/repository. (Fares, M., Kutuzov, A., Oepen, S., & Velldal, E. (2017). Word vectors, reuse, and replicability: Towards a community repository of large-text resources. Proceedings of the 21st Nordic Conference on Computational Linguistics, Gothenburg, Sweden.) |
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3) The folder resources/outputs/final_decoder_outputs contains the final generated text per decoding strategy (Greedy decoding, Top-p & top-k, or Beam search) for both the full test set and the sample dataset |
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4) The folder translations contains sampled text (106 and 84 rows) from the original English datasets (WIKILarge and ASSET), a machine-translated version as well as the human translated references. |
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# Credits |
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The preprocessor.py and the utils.py contain code that has been adapted from https://github.com/KimChengSHEANG/TS_T5 (Sheang, K. C., & Saggion, H. (2021). Controllable Sentence Simplification with a Unified Text-to-Text Transfer Transformer.INLG 2021 International Conference on Natural Language Generation, Aberdeen, Scotland, UK.) |
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The preprocessor.py has been adapted to the usage of Dutch. |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** Theresa Seidl |
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- **Funded by [optional]:** [More Information Needed] |
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- **Shared by [optional]:** [More Information Needed] |
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- **Model type:** [More Information Needed] |
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- **Language(s) (NLP):** Dutsch |
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- **License:** [More Information Needed] |
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- **Finetuned from model [optional]:** https://huggingface.co/yhavinga/t5-base-dutch |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** https://github.com/tsei902/simplify_dutch |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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# |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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[More Information Needed] |
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### Downstream Use [optional] |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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[More Information Needed] |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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[More Information Needed] |
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## Bias, Risks, and Limitations |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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[More Information Needed] |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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[More Information Needed] |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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[More Information Needed] |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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[More Information Needed] |
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#### Training Hyperparameters |
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- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
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#### Speeds, Sizes, Times [optional] |
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<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. --> |
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[More Information Needed] |
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## Evaluation |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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### Testing Data, Factors & Metrics |
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#### Testing Data |
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<!-- This should link to a Dataset Card if possible. --> |
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[More Information Needed] |
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#### Metrics |
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<!-- These are the evaluation metrics being used, ideally with a description of why. --> |
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[More Information Needed] |
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### Results |
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[More Information Needed] |
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#### Summary |
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### Model Architecture and Objective |
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[More Information Needed] |
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### Compute Infrastructure |
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[More Information Needed] |
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#### Hardware |
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[More Information Needed] |
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## Citation [optional] |
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<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. --> |
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**BibTeX:** |
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[More Information Needed] |
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**APA:** |
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[More Information Needed] |
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