Enhanced Bertweet and Sentiment_data#6
Open
dino65-dev wants to merge 2 commits into
Open
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
issue: #7
Changes of Enhancement made into :
Bertweet_model.py
Error Handling: Added comprehensive error handling during model initialization and inference.
Documentation: Expanded docstrings with detailed information on parameters, return values, and exceptions.
Type Hints: Added comprehensive type annotations following PEP-484 for better IDE support.
Caching Mechanism: Implemented
lru_cachefor tokenization to improve performance for repeated texts.Batch Processing: Added a dedicated
batch_processmethod to handle multiple texts efficiently.Evaluation Capability: Added an
evaluatemethod to assess model performance against ground truth.Logging System: Replaced print statements with proper logging for better debug information.
Model Persistence: Added methods to save and load models for reuse.
Progress Tracking: Integrated tqdm for progress visualization during batch processing.
Improved Initialization: Better organization of initialization code and class structure.
Device Management: Automatic device selection (CUDA if available).
Graceful Failure Handling: The model now returns default values instead of crashing on errors.
Expanded Testing Code: More comprehensive examples in the
__main__section.Class/Module Organization: Better separation of concerns with helper methods.
Sentiment_data.py
Improved Error Handling: Added comprehensive exception handling and validation of inputs.
Logging System: Replaced print statements with proper logging for better monitoring and debugging.
Type Annotations: Added comprehensive type hints for better code editor support and documentation.
Result Caching: Added
lru_cacheto improve performance for repeated analysis of the same text.Batch Processing: Enhanced batch processing capabilities with progress tracking.
More Detailed Results: Added options to include probabilities for all sentiment classes in results.
Empty Input Handling: Now properly handles empty text inputs.
Improved Documentation: Added comprehensive docstrings for all methods.
Model Information: Added method to retrieve information about the loaded model.
Cache Management: Added methods to clear and manage the sentiment analysis cache.
Processing Time Tracking: Added timing information to see how long analysis took.
Sample Analysis: Added utility method to quickly verify model functionality.
Expanded Test Code: The
__main__section now includes more comprehensive examples.Pretty Printing: Added better formatting for demo output.
Error State Results: Ensures results always include label and confidence, even in error cases.