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---
license: apache-2.0
datasets:
- winddude/finacial_pharsebank_66agree_split
- financial_phrasebank
language:
- en
base_model:
- state-spaces/mamba-2.8b
metrics:
- accuracy
- f1
- recall
- precission
model-index:
- name: financial-sentiment-analysis
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: financial_phrasebank
type: financial_phrasebank
args: sentences_66agree
metrics:
- name: Accuracy
type: accuracy
value: 0.82
- name: Percision
type: percision
value: 0.82
- name: recall
type: recall
value: 0.82
- name: F1
type: f1
value: 0.82
pipeline_tag: text-classification
tags:
- finance
---
# Mamba Financial Headline Sentiment Classifier
A sentment classifier for finacial headlines using mamba 2.8b as the base model.
Text is classified into 1 of 3 labels; positive, neutral, or negative.
## Prompt Format:
```
prompt = f"""Classify the setiment of the following news headlines as either `positive`, `neutral`, or `negative`.\n
Headline: {headline}\n
Classification:"""
```
where `headline` is the text you want to be classified. |