You can deploy this model and start earning money today!

Sanjeev2501/
nyxar-bilstm-sentiment

Name: nyxar-bilstm-sentiment
Availability: InStock

keras

text-classification

SetFit/amazon_reviews_multi_en

mit

Views

No views yet

NYXAR BiLSTM Sentiment Model

Model Description

A deep learning sentiment classification model developed for the NYXAR AI Intelligence & Observability Platform.

The model uses a Bidirectional Long Short-Term Memory (BiLSTM) neural network to capture contextual information from text sequences and predict sentiment across three classes:

Positive
Neutral
Negative

Framework:

TensorFlow
Keras
BiLSTM Architecture

Language:

English

License:

Training Data

Dataset:

SetFit/amazon_reviews_multi_en

The dataset contains English Amazon product reviews used for sentiment classification.

Intended Use

This model is designed for:

Customer feedback analysis
Product review monitoring
Support ticket intelligence
Sentiment trend analysis

Limitations

The model may struggle with:

Sarcasm
Irony
Ambiguous sentiment
Domain-specific terminology not represented in the training data

Predictions should be used as supporting signals rather than business-critical decisions.

Performance

Metrics obtained during evaluation:

Accuracy: 72.82%
Precision: 70.55%
Recall: 72.82%
F1 Score: 71.29%

Usage

python

import joblib
from tensorflow.keras.models import load_model
from tensorflow.keras.preprocessing.sequence import pad_sequences

model = load_model("bilstm_model_v1.keras")

tokenizer = joblib.load("bilstm_tokenizer_v1.pkl")
max_len = joblib.load("max_len_v1.pkl")

text = ["The product exceeded expectations."]

sequence = tokenizer.texts_to_sequences(text)
padded = pad_sequences(sequence, maxlen=max_len)

prediction = model.predict(padded)

Sanjeev2501/nyxar-bilstm-sentiment