SEBIS/code_trans_t5_large_commit_generation_transfer_learning_finetune

This model is trained on tokenized git commit: it works best with tokenized commit . It can be used on unparsed and untokenized commit changes . It has a total of approximately 220M parameters and was trained using the encoder-decoder architecture . The model was then fine-tuned on a single TPU Pod V2-8 for 4,000 steps in total, using sequence length 512 (batch size 256) The model could be used to generate the git commit message for the commit changes or for other relevant tasks . The code is based on the t5-large model and has its own SentencePiece vocabulary model . It used transfer-learning pre-,