Text Classification
Transformers
PyTorch
Safetensors
French
camembert
financial-sentiment-analysis
sentiment-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use bardsai/finance-sentiment-fr-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bardsai/finance-sentiment-fr-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="bardsai/finance-sentiment-fr-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("bardsai/finance-sentiment-fr-base") model = AutoModelForSequenceClassification.from_pretrained("bardsai/finance-sentiment-fr-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
docs: add MIT license (inherited from CamemBERT), base_model + metadata per HF guidelines
Browse files
README.md
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---
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language:
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tags:
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- text-classification
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- financial-sentiment-analysis
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- sentiment-analysis
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datasets:
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metrics:
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- f1
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- accuracy
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example_title: "Example 2"
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- text: "Les actions de CDPROJEKT ont enregistré la plus forte baisse parmi les entreprises cotées au WSE."
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example_title: "Example 3"
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---
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## Changelog
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- 2023-09-18: Initial release
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## About bards.ai
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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/)
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---
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language:
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- fr
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license: mit
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library_name: transformers
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pipeline_tag: text-classification
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tags:
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- text-classification
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- financial-sentiment-analysis
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- sentiment-analysis
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- camembert
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base_model: camembert-base
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datasets:
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- financial_phrasebank
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metrics:
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- f1
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- accuracy
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example_title: "Example 2"
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- text: "Les actions de CDPROJEKT ont enregistré la plus forte baisse parmi les entreprises cotées au WSE."
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example_title: "Example 3"
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model-index:
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- name: finance-sentiment-fr-base
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results:
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- task:
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type: text-classification
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name: Financial Sentiment Analysis
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dataset:
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name: Financial PhraseBank (translated to French)
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type: financial_phrasebank
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metrics:
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- type: f1
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value: 0.963
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name: F1 (macro)
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- type: precision
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value: 0.959
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name: Precision (macro)
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- type: recall
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value: 0.967
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name: Recall (macro)
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- type: accuracy
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value: 0.971
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name: Accuracy
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---
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## Changelog
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- 2023-09-18: Initial release
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## License
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This model is released under the **[MIT License](https://opensource.org/licenses/MIT)**, inherited from the base model [camembert-base](https://huggingface.co/camembert-base) (MIT).
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Attribution: CamemBERT — Inria, Facebook AI Research; Finance Sentiment FR (base) — bards.ai.
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## About bards.ai
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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/)
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