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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!")
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