SEBIS/code_trans_t5_large_api_generation_multitask_finetune

The CodeTrans model is based on the t5-large model architecture . It has its own SentencePiece vocabulary model . It used multi-task training on 13 supervised tasks in the software development domain and 7 unsupervised datasets . It is then fine-tuned on the api recommendation generation task for the java apis. The model could be used to generate API usage for the . java programming tasks. It has a total of approximately 220M parameters and was trained using the encoder-decoder architecture. The optimizer used is AdaFactor with inverse square root learning rate schedule for pre-training. It was trained on a single TPU Pod V3-8 for 500,,