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Enhancing BERT Training: The development of AI features and advanced techniques has been addressed as the next step to be integrated #108

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Enhancing BERT Training: The development of AI features and advanced techniques has been addressed as the next step to be integrated #108

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Commits on Aug 23, 2024

  1. BERT_Training_Enhanced.py 

    This commit introduces several key updates to the BERT training script to enhance its functionality, integrate new AI features, and resolve existing issues.

Key Changes:

Integration of Advanced AI Features:
The script has been enhanced with new AI-driven features, improving the training process's efficiency and accuracy. These include optimizations to model training, hyperparameter tuning, and error handling mechanisms.

EarlyStopping Implementation:
We have added the EarlyStopping feature, which helps in preventing overfitting by stopping the training when the validation loss stops improving. This is particularly useful for models that are prone to overtraining on the dataset.

Resolved Undefined Variable Error:
The script previously contained an error where the EarlyStopping class was referenced without being defined. This issue has been addressed by importing the appropriate class from the necessary module, ensuring the script runs without errors.

Refinement of Argument Parsing:
The argument parsing section was refined to better handle various input configurations. This includes adjustments to default values and validation checks to ensure robust execution.

Improved Documentation:
Inline comments and documentation strings were added to clarify the purpose and functionality of each section of the code, making it easier for future developers to understand and modify the script.

Optimized Data Loading Process:
The data loading process was optimized to reduce memory usage and increase processing speed. This includes adjustments to the DataLoader parameters and better management of on-memory operations.

Enhancement of Model Training Loop:
The model training loop was modified to incorporate the newly added AI features, such as dynamic learning rate adjustments and automated early stopping. These changes aim to improve the overall model performance and reduce training time.

Impact:
These updates significantly enhance the script's functionality, making it more robust, efficient, and user-friendly. The integration of AI features and the resolution of existing errors ensure that the model training process is smoother and yields better results.
    @RahulVadisetty91
    RahulVadisetty91 authored Aug 23, 2024
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  2. Merge pull request #1 from RahulVadisetty91/RahulVadisetty91-patch-1 

    Enhancements to BERT Training Script: AI Features Integration and Bug Fixes
    @RahulVadisetty91
    RahulVadisetty91 authored Aug 23, 2024
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