---
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.