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The paper describes the work that the team submitted to FinCausal 2020 SharedTask. This work is associated with the first sub-task of identifying causalityin sentences. The various models used in the experiments tried to obtain alatent space representation for each of the sentences. Linear regression wasperformed on these representations to classify whether the sentence is causalor not. The experiments have shown BERT (Large) performed the best, giving a F1score of 0.958, in the task of detecting the causality of sentences infinancial texts and reports. The class imbalance was dealt with a modified lossfunction to give a better metric score for the evaluation.

IIT_kgp at FinCausal 2020, Shared Task 1: Causality Detection using Sentence Embeddings in Financial Reports