đ fine-tuned-cardiffnlp-twitter-roberta-base-sentiment-finance-dataset
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment for sentiment analysis of Twitter finance news, providing high accuracy in sentiment classification.
đ Quick Start
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment on an twitter finance news sentiment dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3123
- Accuracy: 0.8559
10 examples in Inference API are gathered from https://twitter.com/ftfinancenews in early may 2024
Colab Notebook for fine tuning : https://colab.research.google.com/drive/1gvpFbazlxg3AdSldH3w6TYjGUByxqCrh?usp=sharing
đ Documentation
Training Data
https://huggingface.co/datasets/CJCJ3030/twitter-financial-news-sentiment/viewer/default/train
Evaluation Data
https://huggingface.co/datasets/CJCJ3030/twitter-financial-news-sentiment/viewer/default/validation
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 120
- eval_batch_size: 120
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Epoch |
Step |
Validation Loss |
Accuracy |
1.0 |
80 |
0.3123 |
0.8559 |
2.0 |
160 |
0.3200 |
0.8576 |
3.0 |
240 |
0.3538 |
0.8819 |
4.0 |
320 |
0.3695 |
0.8882 |
5.0 |
400 |
0.4108 |
0.8869 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
đ License
Citation
@inproceedings{barbieri-etal-2020-tweeteval,
title = "{T}weet{E}val: Unified Benchmark and Comparative Evaluation for Tweet Classification",
author = "Barbieri, Francesco and
Camacho-Collados, Jose and
Espinosa Anke, Luis and
Neves, Leonardo",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2020",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.findings-emnlp.148",
doi = "10.18653/v1/2020.findings-emnlp.148",
pages = "1644--1650"
}
đ Information Table
Property |
Details |
Model Type |
Fine-tuned version of cardiffnlp/twitter-roberta-base-sentiment |
Training Data |
https://huggingface.co/datasets/CJCJ3030/twitter-financial-news-sentiment/viewer/default/train |
Evaluation Data |
https://huggingface.co/datasets/CJCJ3030/twitter-financial-news-sentiment/viewer/default/validation |
Metrics |
Loss: 0.3123, Accuracy: 0.8559 |
Training hyperparameters |
learning_rate: 5e-05, train_batch_size: 120, eval_batch_size: 120, seed: 42, optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08, lr_scheduler_type: linear, num_epochs: 5 |
Framework versions |
Transformers 4.40.2, Pytorch 2.2.1+cu121, Datasets 2.19.1, Tokenizers 0.19.1 |