my-sentiment-analyzer

Fine-tuned distilbert-base-uncased for binary sentiment classification (0 = negative, 1 = positive).

Evaluation Results

Metric Score
Accuracy 0.877
Precision 0.869
Recall 0.887
F1 0.878

Usage

from transformers import pipeline
classifier = pipeline("sentiment-analysis", model="Hannia67/my-sentiment-analyzer")
result = classifier("This was a great experience!")
print(result)
Downloads last month
4
Safetensors
Model size
67M params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Dataset used to train Hannia67/my-sentiment-analyzer

Space using Hannia67/my-sentiment-analyzer 1