chinmaygarde/hello

DistilBERT Sentiment Classifier (IMDB)

Fine-tuned distilbert-base-uncased for binary sentiment classification (positive/negative) on a subset of the IMDB movie review dataset.

Model Details

• Base model: distilbert/distilbert-base-uncased
• Task: Sentiment analysis (binary classification)
• Labels: 0 = negative, 1 = positive
• Max sequence length: 128 tokens

Training

Hyperparameter	Value
Dataset	IMDB (500 samples, 80/20 split)
Epochs	2
Batch size	8
Learning rate	5e-5 (linear decay)

Final eval loss: 0.0008

Usage

from transformers import pipeline

classifier = pipeline("text-classification", model="chinmaygarde/hello")
classifier("This movie was absolutely fantastic!")
# [{'label': 'LABEL_1', 'score': 0.999}]