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SemEval Task 2: Predicting Valence-Arousal Score for Longitudinal Texts

Environment set up

  1. Create a new python virtual environment on your machine and activate

  2. Install PyTorch using the official instruction: https://pytorch.org/

  3. Run pip install -r requirements.txt to install the rest of the libraries

Running the inference

Subtask 1

python BiLSTM_predict.py --valence_model models/subtask1_val.pt --arousal_model models/subtask1_aro.pt --input .\data\test_subtask1.csv --output pred_subtask1.csv

Subtask 2a

python tft_subtask2a.py

Subtask 2b

python lm_rnn_subtask2b.py

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Official repository for UAlberta at SemEval-2026 Task 2: Predicting Variation in Emotional Valence and Arousal over Time from Ecological Essays

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