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bardsai/twitter-sentiment-pl-fast

sourceHugging Faceapache-2.0updated 5mo agoView on Hugging Face

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Twitter Sentiment PL (fast)

Twitter Sentiment PL (fast) is a model based on distiluse for analyzing sentiment of Polish twitter posts. It was trained on the translated version of TweetEval by Barbieri et al., 2020 for 10 epochs on single RTX3090 gpu

The model will give you a three labels: positive, negative and neutral.

How to use

You can use this model directly with a pipeline for sentiment-analysis:

python

from transformers import pipeline

nlp = pipeline("sentiment-analysis", model="bardsai/twitter-sentiment-pl-fast")
nlp("Szczęście i Opatrzność mają znaczenie Gratuluje @pzpn_pl")

bash

[{'label': 'positive', 'score': 0.9965680837631226}]

Performance

Metric	Value
f1 macro	0.570
precision macro	0.570
recall macro	0.575
accuracy	0.582
samples per second	225.9

(The performance was evaluated on RTX 3090 gpu)

Changelog

—2023-07-19: Initial release

License

This model is released under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0), inherited from the base model sentence-transformers/distiluse-base-multilingual-cased-v1 (Apache 2.0).

Attribution: distiluse-base-multilingual-cased-v1 — Sentence-Transformers (UKP Lab); Twitter Sentiment PL (fast) — bards.ai.

About bards.ai

At bards.ai, we focus on providing machine learning expertise and skills to our partners, particularly in the areas of nlp, machine vision and time series analysis. Our team is located in Wroclaw, Poland. Please visit our website for more information: bards.ai

Let us know if you use our model :). Also, if you need any help, feel free to contact us at info@bards.ai