PyTorch models for polish language sentiment regression based on allegro/herbert and CLARIN-PL dataset
Project description
sentimentPL
PyTorch models for polish language sentiment regression based on allegro/herbert and CLARIN-PL dataset
Installation
sentimentPL is available on PyPI, so You can just run:
$ pip3 install sentimentpl
Basic Usage
For a given sentence, the model produces output value from (-1;1) range (from most negative to most positive).
from sentimentpl.models import SentimentPLModel
model = SentimentPLModel(from_pretrained='latest')
print(model('Jestem wesoły Romek').item())
Note: The model uses transformers API to load pretrained embedding models from their repository. They should be downloaded and cached on Your machine.
Note: The model loads pretrained state dicts for final regression layers from a file included in the package files (as its size does not exceed 1MB). This will be changed in the future, so the model would be loaded from external repository.
Training
For training You would probably want to download the source code by cloning the repository:
$ git clone https://github.com/philvec/sentimentPL.git
Download training data from
https://clarin-pl.eu/dspace/bitstream/handle/11321/710/dataset_conll.zip
and unzip it to sentimentpl/data.
In the main repository dir, run
$ python3 ./sentimentpl/train.py
Version history
v.0.0.3 latest
Basic 3-layer MLP with ReLU and input Dropout.
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