Three classes sentiment analysis (positive, negative, neutral)
Based on https://huggingface.co/j-hartmann/sentiment-roberta-large-english-3-classes
Fine-tuned using:
- annotated sentences from book reviews in English https://www.gti.uvigo.es/index.php/en/book-reviews-annotated-dataset-for-aspect-based-sentiment-analysis
- annotated paragraphs from amateur writers' stories https://arxiv.org/abs/1910.11769
Performance for books:
Num examples = 1666
Batch size = 16
precision | recall | f1-score | support | |
---|---|---|---|---|
Negative | 0.83 | 0.88 | 0.85 | 844 |
Neutral | 0.68 | 0.51 | 0.58 | 351 |
Positive | 0.79 | 0.85 | 0.82 | 471 |
accuracy | 0.79 | 1666 | ||
macro avg | 0.76 | 0.75 | 0.75 | 1666 |
weighted avg | 0.78 | 0.79 | 0.78 | 1666 |
Performance for reviews:
Num examples = 205
Batch size = 16
precision | recall | f1-score | support | |
---|---|---|---|---|
Negative | 0.89 | 0.92 | 0.91 | 26 |
Neutral | 0.96 | 0.91 | 0.94 | 90 |
Positive | 0.94 | 0.98 | 0.96 | 89 |
accuracy | 0.94 | 205 | ||
macro avg | 0.93 | 0.94 | 0.93 | 205 |
weighted avg | 0.94 | 0.94 | 0.94 | 205 |
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