π¬ IMDB Bi-LSTM Sentiment Classifier
Predicts whether a movie review is positive (π) or negative (π) using a compact bidirectional LSTM built in PyTorch.
Detail | Value |
---|---|
Sequence length cap | 500 tokens |
Vocabulary size | 5 000 word stems |
Embedding dim | 256 |
LSTM | 2 layers Β· 256 hidden Β· bidirectional |
Parameters | ~6 M |
Validation accuracy | 0.8651 |
Test AUC | 0.9299 |
Quick start
# pip install huggingface_hub torch nltk
from huggingface_hub import hf_hub_download
from inference import predict # ships with the repo files
hf_hub_download("ecroatt/imdb-bilstm-sentiment", "pytorch_model.bin")
print(predict("Terrific cast and a heart-warming story!"))
# 0.96 -> positive
print(predict("I was bored out of my mind; worst sequel ever."))
# 0.04 -> negative
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Dataset used to train ecroatt/imdb-bilstm-sentiment
Space using ecroatt/imdb-bilstm-sentiment 1
Evaluation results
- Accuracy on IMDB Large Movie Review Datasetself-reported0.865
- F1 on IMDB Large Movie Review Datasetself-reported0.864
- AUC on IMDB Large Movie Review Datasetself-reported0.930