middle-dutch-NER_text-classification

Model description

Middle Dutch NER with PassiveAgressiveClassifier

Intended uses & limitations

This model is not ready to be used in production.

Training Procedure

TESTING

Hyperparameters

The model is trained with below hyperparameters.

<details> <summary> Click to expand </summary> </details>

Model Plot

The model plot is below.

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See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id="sk-container-id-1" class="sk-top-container" style="overflow: auto;"><div class="sk-text-repr-fallback"><pre>Pipeline(steps=[(&#x27;trans&#x27;,FunctionTransformer(func=&lt;function revert_data at 0x7f3fb95883a0&gt;)),(&#x27;vectorizer&#x27;, CountVectorizer()),(&#x27;classifier&#x27;, PassiveAggressiveClassifier(random_state=42))])</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class="sk-container" hidden><div class="sk-item sk-dashed-wrapped"><div class="sk-label-container"><div class="sk-label sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-1" type="checkbox" ><label for="sk-estimator-id-1" class="sk-toggleable__label sk-toggleable__label-arrow">Pipeline</label><div class="sk-toggleable__content"><pre>Pipeline(steps=[(&#x27;trans&#x27;,FunctionTransformer(func=&lt;function revert_data at 0x7f3fb95883a0&gt;)),(&#x27;vectorizer&#x27;, CountVectorizer()),(&#x27;classifier&#x27;, PassiveAggressiveClassifier(random_state=42))])</pre></div></div></div><div class="sk-serial"><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-2" type="checkbox" ><label for="sk-estimator-id-2" class="sk-toggleable__label sk-toggleable__label-arrow">FunctionTransformer</label><div class="sk-toggleable__content"><pre>FunctionTransformer(func=&lt;function revert_data at 0x7f3fb95883a0&gt;)</pre></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-3" type="checkbox" ><label for="sk-estimator-id-3" class="sk-toggleable__label sk-toggleable__label-arrow">CountVectorizer</label><div class="sk-toggleable__content"><pre>CountVectorizer()</pre></div></div></div><div class="sk-item"><div class="sk-estimator sk-toggleable"><input class="sk-toggleable__control sk-hidden--visually" id="sk-estimator-id-4" type="checkbox" ><label for="sk-estimator-id-4" class="sk-toggleable__label sk-toggleable__label-arrow">PassiveAggressiveClassifier</label><div class="sk-toggleable__content"><pre>PassiveAggressiveClassifier(random_state=42)</pre></div></div></div></div></div></div></div>

Evaluation Results

You can find the details about evaluation process and the evaluation results.

Confusion Matrix

How to Get Started with the Model

[More Information Needed]

Model Card Authors

Alassea TEST

Model Card Contact

You can contact the model card authors through following channels: [More Information Needed]

Citation

BibTeX

@inproceedings{...,year={2022}}