Instructions to use bardsai/finance-sentiment-pl-fast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-pl-fast with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-pl-fast")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-pl-fast") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-pl-fast") - Notebooks
- Google Colab
- Kaggle
Finance Sentiment PL (fast)
Finance Sentiment PL (fast) is a distiluse-based model for analyzing sentiment of Polish financial news. It was trained on the translated version of Financial PhraseBank by Malo et al. (2014) 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:
from transformers import pipeline
nlp = pipeline("sentiment-analysis", model="bardsai/finance-sentiment-pl-fast")
nlp("Sprzedaż netto wzrosła o 30% do 36 mln EUR.")
[{'label': 'positive', 'score': 0.9999998807907104}]
Performance
| Metric | Value |
|---|---|
| f1 macro | 0.933 |
| precision macro | 0.950 |
| recall macro | 0.918 |
| accuracy | 0.944 |
| samples per second | 268.1 |
(The performance was evaluated on RTX 3090 gpu)
Changelog
- 2022-12-01: Rename the model to finance-sentiment-pl-base
- 2022-11-15: Initial release
License
This model is released under the Apache 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); Finance 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
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Evaluation results
- F1 (macro) on Financial PhraseBank (translated to Polish)self-reported0.933
- Precision (macro) on Financial PhraseBank (translated to Polish)self-reported0.950
- Recall (macro) on Financial PhraseBank (translated to Polish)self-reported0.918
- Accuracy on Financial PhraseBank (translated to Polish)self-reported0.944