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distilbert-rotten-tomatoes-sentiment – AI Model by Nav772 | AlphaNeural AI

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Nav772/
distilbert-rotten-tomatoes-sentiment

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sentiment-analysis

text-classification

rotten_tomatoes

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DistilBERT Fine-tuned on Rotten Tomatoes

Model Description

This model is a fine-tuned version of distilbert-base-uncased for binary sentiment classification (positive/negative movie reviews).

Training Data

Dataset: Rotten Tomatoes movie reviews
Train samples: 8,530
Test samples: 1,066

Training Procedure

Base model: distilbert-base-uncased
Epochs: 3
Batch size: 16
Learning rate: 2e-5
Max sequence length: 128

Evaluation Results

Accuracy: ~85% on test set

Usage

python

from transformers import pipeline

classifier = pipeline("sentiment-analysis", model="Nav772/distilbert-rotten-tomatoes-sentiment")
result = classifier("This movie was great!")
print(result)

Limitations

Trained only on movie reviews; may not generalize to other domains
English language only
Binary classification only (no neutral category)