emiltj / DaCy-3.0.0

🪐 spaCy Project: Train spaCy transformer for Danish

This project template lets you train a Named-Entity Recognition model on the DANSK dataset. It takes care of downloading the corpus and trains and evaluates the model. The template uses one of more of the transformer models which have been downloaded via Huggingface:

• "jonfd/electra-small-nordic"
• "NbAiLab/nb-roberta-base-scandi",
• "KennethEnevoldsen/dfm-bert-large-v1-2048bsz-1Msteps"ßß

You can run from yaml file using spacy project run WORKFLOW/COMMAND

📋 project.yml

The project.yml defines the data assets required by the project, as well as the available commands and workflows. For details, see the spaCy projects documentation.

⏯ Commands

The following commands are defined by the project. They can be executed using spacy project run [name]. Commands are only re-run if their inputs have changed.

Command	Description
fetch_assets	Downloads DANSK to assets/
split_dansk	Splits DANSK into train, dev, test
train	Trains test DaCy model
evaluate	Evaluate the test model on the test.spacy and save the metrics
package	Package the test trained model so it can be installed
publish	Publish test package to huggingface model hub.
train_all_models	Trains DaCy models of small, medium and large
evaluate_all_models	Evaluate all models on the test.spacy and save the metrics
package_all_models	Package all trained models so they may be installed
publish_all_models	Publish all model packages to huggingface model hub.
generate_readme	Auto-generates a README.md with a project description.
clean	Remove intermediate files

⏭ Workflows

The following workflows are defined by the project. They can be executed using spacy project run [name] and will run the specified commands in order. Commands are only re-run if their inputs have changed.

Workflow	Steps
train_eval_pack_publ	train → evaluate → package → publish
all_models_train_eval_pack_publ	train_all_models → evaluate_all_models → package_all_models → publish_all_models

🗂 Assets

The following assets are defined by the project. They can be fetched by running spacy project assets in the project directory.

File	Source	Description
assets/	Local