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Semantic Role Labeling project with 88.8% F1-score on English, 77.04% on French and 78.68% on Spanish. The dataset used in this task is the UniteD-SRL dataset. I developed it in Pytorch using Transformers, BiLSTMs and pos embeddings.

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NLP course a.y. 2021/22: Homework #2

Semantic Role Labeling project that reached 88.8% F1-score on English, 77.04% F1 on French and 78.68% on Spanish. This was the top-scoring homework of the class. The dataset used in this task is the UniteD-SRL dataset, which is private. I developed it in Pytorch using Transformers, BiLSTMs and pos embeddings. This was the second homework of the NLP 2022 course at Sapienza University of Rome.

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Semantic Role Labeling project with 88.8% F1-score on English, 77.04% on French and 78.68% on Spanish. The dataset used in this task is the UniteD-SRL dataset. I developed it in Pytorch using Transformers, BiLSTMs and pos embeddings.

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