Update README.md

README.md

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-We fine tune jjzha/esco-xlm-roberta-large for the sentence level binary skill identification. The findings reveal 94% accuracy and F1-score. The findings reveal effectiveness of the model for the cross-lingual transfer. Please refer to the original paper for the more information, and if you use this work please cite the following: 
+We fine-tune jjzha/esco-xlm-roberta-large for sentence-level binary skill identification. The results show 94% accuracy and F1 score in English. Furthermore, the study demonstrates the model's effectiveness for cross-lingual transfer. Please refer to the original paper for more information, and if you use this work, please cite the following:
 
 Musazade, N., Zhang, M., & Mezei, J. (2025, August). Cross-Lingual Sentence-Level Skill Identification in English and Danish Job Advertisements. In Proceedings of the 8th International Conference on Natural Language and Speech Processing (ICNLSP-2025) (pp. 410-415).