Sentiment Analysis On Dynasent

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Macro F1

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

		Paper Title
GPT-4o Fine-Tuned (Minimal)	89	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o-mini Fine-Tuned	86.9	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o + ELECTRA Large FT (Prompt, Label, Examples)	81.53	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o (Prompt)	80.22	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o-mini + ELECTRA Large FT (Prompt, Label, Probabilities)	79.72	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o-mini + ELECTRA Large FT (Prompt, Label)	77.94	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o + ELECTRA Large FT	77.69	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o-mini (Prompt)	77.35	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
ELECTRA Large Fine-Tuned	76.29	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
GPT-4o-mini + ELECTRA Base FT	76.19	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
ELECTRA Base Fine-Tuned	71.83	ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
SVM	-	Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM

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Sentiment Analysis On Dynasent | SOTA | HyperAI