dogruermikail/bert-fine-tuned-stock-sentiment-uncased

Bert Uncased Model Fine Tuned For Stock Sentiment

This model is a fine-tuned version of the BERT (Bidirectional Encoder Representations from Transformers) model specifically designed for analyzing stock sentiment. The fine-tuning process involved training the model on tagged comments from the last two pages of the stock form on the Investing platform, focusing on stocks listed in the BIST Index.

Stock List:

ACSEL, ADEL, ARCLK, ASELS, AZTEK, BIMAS, BFREN, BMSCH,
CCOLA, CIMSA, CMBTN, CWENE,EKGYO, ENJSA, EREGL, FROTO,
GOODY, GUBRF, HALKB, HEKTS, ISCTR, KCHOL, KOZAL, KOPOL,
KRDMD, ONCSM, PETKM, PKART, SAHOL, SASA, SISE, SMRTG,
THYAO, TMSN, TCELL, TTKOM, TOASO, TTRAK, TUPRS, VESTL, YAPRK, YKSLN

This fine-tuned model aims to provide insights into the sentiment of these stocks based on the given tagged comments and can be used for stock sentiment analysis in financial applications.

Colab File

Training hyperparameters

Training Hyperparameters: The following hyperparameters were used during training:

Optimizer: SGD
Learning Rate: 3e-2
Number of Training Epochs: 10
Metric for Best Model: F1 Score

Training Results

Epoch	Training Loss	Validation Loss	Accuracy	Precision	Recall	F1 Score
1	1.057400	0.895725	0.621538	0.618631	0.612559	0.611949
2	0.908400	0.822652	0.632308	0.644781	0.629953	0.622661
3	0.812100	0.788586	0.656923	0.680735	0.659374	0.650310
4	0.747700	0.737312	0.667692	0.670311	0.668073	0.666547
5	0.712600	0.743018	0.692308	0.710226	0.691384	0.686578
6	0.659200	0.771312	0.670769	0.695524	0.669198	0.662246
7	0.608300	0.733821	0.680000	0.677778	0.678871	0.677992
8	0.575900	0.739905	0.701538	0.702704	0.700902	0.698514
9	0.565200	0.754889	0.692308	0.692446	0.693058	0.691157
10	`0.541000`	`0.754683`	`0.704615`	`0.705291`	`0.704209`	`0.702093`

Evaluation Results

Loss	Accuracy	Precision	Recall	F1 Score	Runtime	Samples/s	Steps/s	Epoch
0.754683	0.704615	0.705291	0.704209	0.702093	3.3869	191.915	24.211	10.0

Framework versions

Transformers 4.30.2
TensorFlow 2.12.0
Tokenizers 0.13.3