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Transformers, a cutting-edge architecture for NLP tasks, provide contextual understanding of text, enabling highly accurate sentiment classification. TensorFlow and Keras libraries were used to build, train, and evaluate the model.\n\n## Environment\n\nThe whole experiment was done in Colab notebook. \n\n## Machine Learning\n\nThe pre-processing and feature engineering is almost the same except padding was done. The whole experiment was done in `Full_Assignment_Transformers_IMDB_Sentiment_Analysis.ipynb` from Data Ingestion till Prediction Pipeline.\n\n## Results\nEvaluation using test dataset as follows:\n\n235/235 - 11s - loss: 0.2903 - accuracy: 0.8815 - 11s/epoch - 47ms/step\n\nloss: 0.290\naccuracy: 0.881\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdi37%2Fimdb-reviews-sentiment-analysis-using-transformers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdi37%2Fimdb-reviews-sentiment-analysis-using-transformers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdi37%2Fimdb-reviews-sentiment-analysis-using-transformers/lists"}