deberta-v3-base-finetuned-finance-text-classification

nickmuchi/deberta-v3-base-finetuned-finance-text-classification

deberta-v3-base-finetuned-finance-text-classification is a text classification model from nickmuchi. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

This model is a fine-tuned version of microsoft/deberta-v3-base on the sentence50Agree financial-phrasebank + Kaggle Dataset, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, po…

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From the Hugging Face model README

deberta-v3-base-finetuned-finance-text-classification

This model is a fine-tuned version of microsoft/deberta-v3-base on the sentence_50Agree financial-phrasebank + Kaggle Dataset, a dataset consisting of 4840 Financial News categorised by sentiment (negative, neutral, positive). The Kaggle dataset includes Covid-19 sentiment data and can be found here: sentiment-classification-selflabel-dataset.

It achieves the following results on the evaluation set:

Loss: 0.7687
Accuracy: 0.8913
F1: 0.8912
Precision: 0.8927
Recall: 0.8913

Model description

More information needed

Intended uses & limitations

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Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
No log	1.0	285	0.4187	0.8399	0.8407	0.8687	0.8399
0.5002	2.0	570	0.3065	0.8755	0.8733	0.8781	0.8755
0.5002	3.0	855	0.4148	0.8775	0.8775	0.8778	0.8775
0.1937	4.0	1140	0.4249	0.8696	0.8699	0.8719	0.8696
0.1937	5.0	1425	0.5121	0.8834	0.8824	0.8831	0.8834
0.0917	6.0	1710	0.6113	0.8775	0.8779	0.8839	0.8775
0.0917	7.0	1995	0.7296	0.8775	0.8776	0.8793	0.8775
0.0473	8.0	2280	0.7034	0.8953	0.8942	0.8964	0.8953
0.0275	9.0	2565	0.6995	0.8834	0.8836	0.8846	0.8834
0.0275	10.0	2850	0.7736	0.8755	0.8755	0.8789	0.8755
0.0186	11.0	3135	0.7173	0.8814	0.8814	0.8840	0.8814
0.0186	12.0	3420	0.7659	0.8854	0.8852	0.8873	0.8854
0.0113	13.0	3705	0.8415	0.8854	0.8855	0.8907	0.8854
0.0113	14.0	3990	0.7577	0.8953	0.8951	0.8966	0.8953
0.0074	15.0	4275	0.7687	0.8913	0.8912	0.8927	0.8913

Framework versions

Transformers 4.19.2
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

Task: Text Classification
Library: transformers
Type: deberta-v2
License: mit
Created: May 29, 2022
Updated: Mar 19, 2023