SentiSynth: Synthetic Data Generation for Sentiment Analysis

SentiSynth explores how synthetic data can improve sentiment analysis models when labeled data is scarce.

Installation

# Clone the repository
git clone https://github.com/yourusername/sentisynth.git
cd sentisynth

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -e .
pip install -r requirements-dev.txt

Usage

More details coming soon!

Project Structure

• sentisynth/: Main package
  • data/: Data loading and processing
  • models/: Model implementations
  • generation/: Synthetic data generation
  • evaluation/: Evaluation metrics and analysis
• tests/: Unit tests
• notebooks/: Jupyter notebooks for exploration
• scripts/: Utility scripts

Training

To run on weftdrive:

  nohup /srv/gpurun.pl python src/senti_synth/cli/01_train_teacher.py configs/teacher/stt2_hf.yaml > ~/scratch/senti_synth/logs/$(date +%Y%m%d_%H%M).log 2>&1 &

Setting up on weftdrive

1. SSH into weftdrive: ssh paramkapur@weftdrive.private.reed.edu
2. Git clone the repository: git clone https://github.com/paramkpr/senti_synth.git
3. Setup the conda environment /srv/conda/bin/conda init and source ~/.bashrc
4. Enter the conda environment conda activate deep-learning
   1. Check what packages are installed conda list
   2. Install the packages for the project pip install -r requirements.txt
   3. Install the project pip install -e .
5. SCP data/clean to weftdrive:~/scratch/data/clean: scp -r data/clean paramkapur@weftdrive.private.reed.edu:~/scratch/paramkapur/data/clean
   1. Ensure that the config file points to the correct path: dataset_path: "~/scratch/data/clean"
6. Setup W&B:
   1. export WANDB_API_KEY="..."
   2. python -m wandb login
7. Create the logs directory and file: mkdir -p ~/scratch/paramkapur/logs and touch ~/scratch/paramkapur/logs/$(date +%Y%m%d_%H%M).log
8. Run the training script: nohup /srv/gpurun.pl python src/cli/01_train_teacher.py configs/teacher/sst2_hf.yaml > ~/scratch/paramkapur/logs/$(date +%Y%m%d_%H%M).log 2>&1 &

/scratch/paramkapur/data/clean/clean

nohup /srv/gpurun.pl python src/cli/01_train_teacher.py configs/teacher/sst2_hf.yaml > ~/scratch/paramkapur/logs/$(date +%Y%m%d_%H%M).log 2>&1 &