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bilstm-goemotions
YatishW79/bilstm-goemotions
bilstm-goemotions is a text classification model from YatishW79. Use it when you need a label for a piece of text. The card lists the license as mit.
Bidirectional LSTM with additive attention for multi-label emotion classification on GoEmotions (28 labels).
Access
Public
Updated Apr 23, 2026
Repo size
14.7 MB
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0
Public
Repo makeup
Click a slice to open those files.
.pt14.5 MB · 99%
At a glance
- Task
- Text Classification
- License
- mit
- Access
- Public
- Created
- Apr 23, 2026
- Updated
- Apr 23, 2026
- SHA
- 24512f16
Try a prompt
Model card
From the Hugging Face model README
BiLSTM + GloVe — GoEmotions Emotion Classifier
Bidirectional LSTM with additive attention for multi-label emotion classification on GoEmotions (28 labels).
CS6120 NLP Project — Northeastern University
Architecture
- GloVe 100d pre-trained embeddings
- 2-layer Bidirectional LSTM (hidden: 256)
- Additive attention pooling
- Per-class threshold tuning on validation set
Performance (GoEmotions test set, 5,427 samples)
| Metric | Score |
|---|---|
| Micro-F1 | 0.5415 |
| Macro-F1 | 0.4548 |
| Subset Accuracy | 0.3055 |
| Hamming Accuracy | 0.9531 |
Files
lstm_model.pt— model weights + config (load withtorch.load)vocab.pkl— vocabulary dictionarythresholds_lstm.pkl— per-class decision thresholds (numpy array, shape 28)
Usage
import torch, pickle
from lstm_model import BiLSTMClassifier # from the Space repo
ckpt = torch.load("lstm_model.pt", map_location="cpu")
cfg = ckpt["config"]
model = BiLSTMClassifier(**cfg)
model.load_state_dict(ckpt["state_dict"])
model.eval()
- Task
- Text Classification
- License
- mit
- Languages
- en
- Created
- Apr 23, 2026
- Updated
- Apr 23, 2026