Papers › ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
ELECTRA and GPT-4o: Cost-Effective Partners for Sentiment Analysis
James P. Beno
Bidirectional transformers excel at sentiment analysis, and Large Language Models (LLM) are effective zero-shot learners. Might they perform better as a team? This paper explores collaborative approaches between ELECTRA and GPT-4o for three-way sentiment classification. We fine-tuned (FT) four models (ELECTRA Base/Large, GPT-4o/4o-mini) using a mix of reviews from Stanford Sentiment Treebank (SST) and DynaSent. We provided input from ELECTRA to GPT as: predicted label, probabilities, and retrieved examples. Sharing ELECTRA Base FT predictions with GPT-4o-mini significantly improved performance over either model alone (82.50 macro F1 vs. 79.14 ELECTRA Base FT, 79.41 GPT-4o-mini) and yielded the lowest cost/performance ratio ($0.12/F1 point). However, when GPT models were fine-tuned, including predictions decreased performance. GPT-4o FT-M was the top performer (86.99), with GPT-4o-mini FT close behind (86.70) at much less cost ($0.38 vs. $1.59/F1 point). Our results show that augmenting prompts with predictions from fine-tuned encoders is an efficient way to boost performance, and a fine-tuned GPT-4o-mini is nearly as good as GPT-4o FT at 76% less cost. Both are affordable options for projects with limited resources.
Code
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Tasks
Datasets
Introduced by this paper, per the archive.
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Sentiment Analysis | DynaSent | GPT-4o Fine-Tuned (Minimal) | Macro F1 | 89 | #1 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o-mini Fine-Tuned | Macro F1 | 86.9 | #2 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o + ELECTRA Large FT (Prompt, Label, Examples) | Macro F1 | 81.53 | #3 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o (Prompt) | Macro F1 | 80.22 | #4 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o-mini + ELECTRA Large FT (Prompt, Label, Probabilities) | Macro F1 | 79.72 | #5 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o-mini + ELECTRA Large FT (Prompt, Label) | Macro F1 | 77.94 | #6 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o + ELECTRA Large FT | Macro F1 | 77.69 | #7 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o-mini (Prompt) | Macro F1 | 77.35 | #8 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | ELECTRA Large Fine-Tuned | Macro F1 | 76.29 | #9 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | GPT-4o-mini + ELECTRA Base FT | Macro F1 | 76.19 | #10 of 12 | Archive leaderboard | report |
| Sentiment Analysis | DynaSent | ELECTRA Base Fine-Tuned | Macro F1 | 71.83 | #11 of 12 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o-mini Fine-Tuned | Macro F1 | 75.68 | #1 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o Fine-Tuned (Minimal) | Macro F1 | 73.99 | #2 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o + ELECTRA Large FT | Macro F1 | 72.94 | #3 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o (Prompt) | Macro F1 | 72.2 | #4 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o + ELECTRA Large FT (Prompt, Label, Examples) | Macro F1 | 72.06 | #5 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o-mini + ELECTRA Large FT (Prompt, Label, Examples) | Macro F1 | 71.98 | #6 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o-mini + ELECTRA Base FT | Macro F1 | 71.72 | #7 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o-mini + ELECTRA Large FT (Prompt, Label) | Macro F1 | 70.99 | #8 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | ELECTRA Large Fine-Tuned | Macro F1 | 70.90 | #9 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | GPT-4o-mini (Prompt) | Macro F1 | 70.67 | #10 of 11 | Archive leaderboard | report |
| Sentiment Analysis | SST-3 | ELECTRA Base Fine-Tuned | Macro F1 | 69.95 | #11 of 11 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o Fine-Tuned (Minimal) | Macro F1 | 86.99 | #1 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o-mini Fine-Tuned | Macro F1 | 86.77 | #2 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o-mini + ELECTRA Large FT (Prompt, Label) | Macro F1 | 83.49 | #3 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o + ELECTRA Large FT (Prompt, Label, Examples) | Macro F1 | 83.09 | #4 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o-mini + ELECTRA Base FT (Prompt, Label) | Macro F1 | 82.74 | #5 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | ELECTRA Large Fine-Tuned | Macro F1 | 82.36 | #6 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o + ELECTRA Large FT (Prompt, Label) | Macro F1 | 81.57 | #7 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o (Prompt) | Macro F1 | 80.14 | #8 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | GPT-4o-mini (Prompt) | Macro F1 | 79.52 | #9 of 10 | Archive leaderboard | report |
| Sentiment Analysis | Sentiment Merged | ELECTRA Base Fine-Tuned | Macro F1 | 79.29 | #10 of 10 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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