bert-fine-tuned-stock-sentiment-uncased

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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

Evaluation Results

Framework versions

• Transformers 4.30.2
• TensorFlow 2.12.0
• Tokenizers 0.13.3