Table 6. Performance of MET detection model using different LLMs and spaCy.
| Dataset | Model | Precision | Recall | F1-score |
|---|---|---|---|---|
| Tweets | BETO | 0.632682 | 0.603598 | 0.617797 |
| ALBETO | 0.528998 | 0.561043 | 0.54455 | |
| DistilBETO | 0.571313 | 0.585950 | 0.578539 | |
| MarIA | 0.551669 | 0.586644 | 0.568619 | |
| BERTIN | 0.596184 | 0.589159 | 0.592651 | |
| spaCy | 0.6099071207 | 0.5130208333 | 0.5572842999 | |
| Headlines | BETO | 0.6452513 | 0.667148 | 0.656017 |
| ALBETO | 0.571177 | 0.6114769 | 0.590640 | |
| DistilBETO | 0.604351 | 0.616269 | 0.610252 | |
| MarIA | 0.651957 | 0.622416 | 0.636844 | |
| BERTIN | 0.624006 | 0.608056 | 0.615928 | |
| spaCy | 0.6363636364 | 0.5651041667 | 0.5986206897 | |
| Total | BETO | 0.701815 | 0.693103 | 0.697432 |
| ALBETO | 0.632689 | 0.628821 | 0.630749 | |
| DistilBETO | 0.639000 | 0.651067 | 0.644978 | |
| MarIA | 0.666136 | 0.670400 | 0.668261 | |
| BERTIN | 0.651033 | 0.644374 | 0.647687 | |
| spaCy | 0.7108066971 | 0.6080729167 | 0.6554385965 |