This project attempts to detect programming languages. The goal of the project is to make a model that could be used generally but it will specifically be used as a sentiment analysis exercise.
We typically compare two models in this project; a pattern matching model and a spaCy NER model.
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.
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 |
|---|---|
preprocess |
Convert the data to spaCy's binary format |
patternmod |
Generate a named entity recognition model based on rules. |
train |
Train a named entity recognition model |
evaluate |
Evaluate the model and export metrics |
package |
Package the trained model so it can be installed |
show-stats |
Show the statistics that compares both models. |
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 |
|---|---|
all |
preprocess → patternmod → train → evaluate |
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/admin.jsonl |
Local | JSONL-formatted training data |