andreasvc/segue-meld-multitask

SEGUE fine-tuned on MELD (multitask sentiment + emotion)

This model is a fine-tuned version of declare-lab/segue-w2v2-base trained jointly on sentiment (3-class) and emotion (7-class) recognition on the MELD dataset (Friends TV show dialogues).

Labels

Sentiment: neutral, positive, negative
Emotion: neutral, surprise, fear, sadness, joy, disgust, anger

Performance (test set)

Task	Weighted F1	Macro F1
Sentiment	0.558	0.519
Emotion	0.475	0.273

Requirements

This model depends on the declare-lab/segue repository, which is not pip-installable. You need to clone it and add it to your path:

git clone https://github.com/declare-lab/segue
# run your scripts from inside the segue/ directory, or:
import sys; sys.path.append('/path/to/segue')

Usage

Download model.pt and inference.py from this repository, then:

from inference import load_segue_multitask, segue_predict
model, processor = load_segue_multitask("model.pt")
sent_probs, emo_probs = segue_predict(model, processor, audio_array, sampling_rate=16000)

Training details

• Base model: declare-lab/segue-w2v2-base
• Dataset: MELD (9989 train / 1109 dev / 2610 test utterances)
• Learning rate: 3e-5, warmup ratio: 0.3, 3 epochs
• Checkpoint averaging: last 10 checkpoints (every 100 steps)
• Multitask loss: 0.5 × sentiment + 0.5 × emotion cross-entropy