Text Classification
Transformers
Safetensors
English
modernbert
financial-sentiment-analysis
sentiment-analysis
financial-news
finance
stocks
trading
finbert-alternative
sentiment
fintech
news
text-embeddings-inference
Instructions to use AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis") model = AutoModelForSequenceClassification.from_pretrained("AnkitAI/FinSense-ModernBERT-Financial-News-Sentiment-Analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload eval/result_finsense.json with huggingface_hub
Browse files- eval/result_finsense.json +32 -0
eval/result_finsense.json
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{
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"base": "answerdotai/ModernBERT-base",
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"seed": 42,
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"smoke": false,
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"test_accuracy": 0.8674948240165632,
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"test_macro_f1": 0.8589082381215416,
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"confusion_matrix": [
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[
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52,
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5,
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3
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],
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"labels": [
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"negative",
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"neutral",
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"positive"
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],
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"split": "stratified 80/10/10, split-seed 42",
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"corpus": "fpb-train",
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"dataset": "financial_phrasebank sentences_50agree"
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}
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