transformers pytorch safetensors bert text-classification sentiment-analysis twitter pl dataset:datasets/tweet_eval autotrain_compatible endpoints_compatible region:us
---
datasets:
- datasets/tweet_eval
language: pl
metrics:
- f1
- accuracy
- precision
- recall
tags:
- text-classification
- sentiment-analysis
- twitter
widget:
- text: Nigdy przegrana nie sprawiła mi takiej radości. Szczęście i Opatrzność mają
    znaczenie Gratuluje @pzpn_pl
  example_title: Example 1
- text: Osoby z Ukrainy zapłacą za życie w centrach pomocy? Sprzeczne prawem UE, niehumanitarne,
    okrutne.
  example_title: Example 2
- text: O której kończycie dzisiaj?
  example_title: Example 3
---


# Twitter Sentiment PL (base)

Twitter Sentiment PL (base) is a model based on [herbert-base](https://huggingface.co/allegro/herbert-base-cased) for analyzing sentiment of Polish twitter posts. It was trained on the translated version of [TweetEval](https://www.researchgate.net/publication/347233661_TweetEval_Unified_Benchmark_and_Comparative_Evaluation_for_Tweet_Classification) 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-base")
nlp("Nigdy przegrana nie sprawiła mi takiej radości. Szczęście i Opatrzność mają znaczenie Gratuluje @pzpn_pl")
```
```bash
[{'label': 'positive', 'score': 0.9997233748435974}]
```

## Performance
| Metric | Value |
| --- | ----------- |
| f1 macro | 0.658 |
| precision macro | 0.655 |
| recall macro | 0.662 |
| accuracy | 0.662 |
| samples per second | 129.9 |

(The performance was evaluated on RTX 3090 gpu)

## Changelog
- 2022-12-01: Initial release
- 2023-07-19: Improvement of translation quality

## 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](https://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
