v1.0.0

[jbeno]

Sentiment 1.0.0 Release

Initial release of project codebase and research for "ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis".

Added

• Data: Merged dataset is published in data directory, with links on README to Hugging Face dataset. Data processing to create the Merged dataset is shown in data_processing.ipynb.
• Classifier Model: PyTorch code with DDP support for BERT-based encoder models with custom pooling and either a classifier head or fully fine-tuned is in classifier.py
• Classifier Fine-Tuning Code: Interactive fine-tuning finetune.py program using PyTorch with DDP support that can be used to train a classifier head or fine-tune any number of layers on BERT, RoBERTa, ELECTRA, etc.
• Classifier Fine-Tune Logs: Logs of ELECTRA Base/Large baselines (classifier head only) and full fine-tunes (all layers) are in electra_finetune
• Fine-Tuned ELECTRA Models: Links on README to fine-tuned ELECTRA models on Hugging Face
• GPT Fine-Tuning Code: Code to process data into JSONL and use OpenAI API to fine-tune GPT models is shared in gpt_finetune_experiments.ipynb
• Experiment Runs: All the research experiments involving GPT are documented in gpt_finetune_experiments.ipynb.
• Experiment Results: The predictions and metrics of each experimental run is published in results. Statistics for hypotheses evaluation are in statistics.
• Research Paper: A PDF of the research paper is included, as well as links to the preprint published on arXiv.

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This discussion was created from the release v1.0.0.