FinEAS: Financial Embedding Analysis of Sentiment šŸ“ˆ

Overview

FinEAS: Financial Embedding Analysis of Sentiment šŸ“ˆ

(SentenceBERT for Financial News Sentiment Regression)

This repository contains the code for generating three models for Finance News Sentiment Analysis.

The models implemented are:

  • A SentenceBERT with simple classifier.
  • A BERT with simple classifier.
  • A simple Bi-directional Long-Short Term Memory (LSTM) network.
  • FinBERT from HuggingFace.
  • SentenceBERT from HuggingFace

Models šŸ¤–

Results āœ…

We used three partitions of the datasets from the February 11th, 2021. 6 months previous to that date, 1 year previous to that date and 2 years previous to the date mentioned.

We also evaluated the models 2 weeks later that date; that is to say, we evaluated from February 12th, 2021 to February 26th, 2021.

The table below shows the results:

FinEAS BERT BiLSTM
6 months 0.0556 0.2124 0.2108
6 months
Next 2 weeks
0.1061 0.2190 0.2194
1 year 0.0654 0.2137 0.2140
1 year
Next 2 weeks
0.1058 0.2191 0.2194
2 years 0.0671 0.2087 0.2086
2 years
Next 2 weeks
0.1065 0.2188 0.2185

The table below shows the results for the HuggingFace models

Dates FinEAS FinBERT
6 months 0.0044 0.0050
12 months 0.0036 0.0034
24 months 0.0033 0.0040

Citing šŸ“£

@misc{gutierrezfandino2021fineas,
      title={FinEAS: Financial Embedding Analysis of Sentiment}, 
      author={Asier GutiƩrrez-FandiƱo and Miquel Noguer i Alonso and Petter Kolm and Jordi Armengol-EstapƩ},
      year={2021},
      eprint={2111.00526},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

License šŸ¤

MIT License.

Copyright 2021 Asier GutiƩrrez-FandiƱo & Jordi Armengol-EstapƩ.

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

Owner
LHF Labs
https://huggingface.co/lhf
LHF Labs
MMFlow is an open source optical flow toolbox based on PyTorch

Documentation: https://mmflow.readthedocs.io/ Introduction English | 简体中文 MMFlow is an open source optical flow toolbox based on PyTorch. It is a part

OpenMMLab 688 Jan 06, 2023
Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021)

RSCD (BS-RSCD & JCD) Towards Rolling Shutter Correction and Deblurring in Dynamic Scenes (CVPR2021) by Zhihang Zhong, Yinqiang Zheng, Imari Sato We co

81 Dec 15, 2022
When are Iterative GPs Numerically Accurate?

When are Iterative GPs Numerically Accurate? This is a code repository for the paper "When are Iterative GPs Numerically Accurate?" by Wesley Maddox,

Wesley Maddox 1 Jan 06, 2022
Time series annotation library.

CrowdCurio Time Series Annotator Library The CrowdCurio Time Series Annotation Library implements classification tasks for time series. Features Suppo

CrowdCurio 51 Sep 15, 2022
Code for 'Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning' (AAAI 2022)

Blockwise Sequential Model Learning Code for 'Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning' (AAAI 2022) For ins

2 Jun 17, 2022
NeurIPS 2021, self-supervised 6D pose on category level

SE(3)-eSCOPE video | paper | website Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation Xiaolong Li, Yijia Weng,

Xiaolong 63 Nov 22, 2022
Fake-user-agent-traffic-geneator - Python CLI Tool to generate fake traffic against URLs with configurable user-agents

Fake traffic generator for Gartner Demo Generate fake traffic to URLs with custo

New Relic Experimental 3 Oct 31, 2022
Jigsaw Rate Severity of Toxic Comments

Jigsaw Rate Severity of Toxic Comments

Guanshuo Xu 66 Nov 30, 2022
1st Solution For NeurIPS 2021 Competition on ML4CO Dual Task

KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a

MEGVII Research 24 Sep 08, 2022
Official code release for: EditGAN: High-Precision Semantic Image Editing

Official code release for: EditGAN: High-Precision Semantic Image Editing

565 Jan 05, 2023
Most popular metrics used to evaluate object detection algorithms.

Most popular metrics used to evaluate object detection algorithms.

Rafael Padilla 4.4k Dec 25, 2022
This repo is duplication of jwyang/faster-rcnn.pytorch

Faster RCNN Pytorch This repo is duplication of jwyang/faster-rcnn.pytorch C/C++ code are removed and easier to study. Python 3.8.5 Ubuntu 20.04.1 LTS

Kim Jihwan 1 Jan 14, 2022
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition

Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model

190 Dec 29, 2022
Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks.

Luminous is a framework for testing the performance of Embodied AI (EAI) models in indoor tasks. Generally, we intergrete different kind of functional

28 Jan 08, 2023
A pytorch reprelication of the model-based reinforcement learning algorithm MBPO

Overview This is a re-implementation of the model-based RL algorithm MBPO in pytorch as described in the following paper: When to Trust Your Model: Mo

Xingyu Lin 93 Jan 05, 2023
MLPs for Vision and Langauge Modeling (Coming Soon)

MLP Architectures for Vision-and-Language Modeling: An Empirical Study MLP Architectures for Vision-and-Language Modeling: An Empirical Study (Code wi

Yixin Nie 27 May 09, 2022
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models

merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept

Pranav 39 Nov 21, 2022
A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising (CVPR 2020 Oral & TPAMI 2021)

ELD The implementation of CVPR 2020 (Oral) paper "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising" and its journal (TPAMI) v

Kaixuan Wei 359 Jan 01, 2023
Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task

multi-task_losses_optimizer Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task å·²ē»å®žéŖŒčæ‡äŗ†ļ¼Œäøä¼šęœ‰cuda out of memoryęƒ…å†µ ##Par

14 Dec 25, 2022
Online-compatible Unsupervised Non-resonant Anomaly Detection Repository

Online-compatible Unsupervised Non-resonant Anomaly Detection Repository Repository containing all scripts used in the studies of Online-compatible Un

0 Nov 09, 2021