metadata
datasets:
- imdb
language: en
license: apache-2.0
metrics:
- accuracy
- f1
pipeline_tag: text-classification
tags:
- sentiment-analysis
- text-classification
- distilbert
sentiment-tutorial
Fine-tuned distilbert-base-uncased for binary sentiment classification.
Intended Use
Classify English text as positive or negative.
Training Procedure
- Base model: distilbert-base-uncased
- Epochs: 2
- Learning rate: 2e-5
- Batch size: 32
- Max length: 128
Evaluation Results
Accuracy: 0.870
Precision: 0.879
Recall: 0.858
F1: 0.868
Limitations
- Binary classification only
- English only
- Movie reviews domain
Usage
from transformers import pipeline
classifier = pipeline( "sentiment-analysis", model="ayesha9f/sentiment-tutorial" )
classifier("This was a great experience!")