Two tasks are proposed at CLEF eRisk-2018 on predicting mental disorder using Users posts on Reddit. Depression and anorexia disorders are considered to be detected as early as possible. In this paper we present the participation of LIRMM (Laboratoire d’Informatique, de Robotique et de Micro´electronique de Montpellier) in both tasks. The proposed architectures and models use only text information without any hand-crafted features or dictionaries to model the temporal mood variation detected from users posts. The proposed models use two learning phases through exploration of state-of-the-art text vectorization. The proposed models perform comparably to other contributions while experiments shows that document-level outperformed word-level vectorizations.