Fine-tune summarization never works well
Hello, guys. I hope you are all good.I am a beginner to Hugging Face, and I am trying to fine-tune a model for a summarization task.I tried bert-multilingual-cased and mT5, but I have the same problem with both of them: the summary does not exceed about 11 words, and they are not good summaries.I used the SAMSum conversational dataset translated into Arabic. I do not know how to solve this problem! I thought by specifyingmax_input_length = 1024andmax_target_length = 128, I would guarantee it works, but it does not, and I cannot figure out where the problem is. You can find the code (I copied a notebook I found from a YouTube video) for fine-tuning here:colab.research.google.comGoogle ColaboratoryCould you please help me find the problem?you can try my model herehuggingface.coshahadalll/mt5-base-finetuned-mt5-summarization-task · Hugging FaceWe’re on a journey to advance and democratize artificial intelligence through open source and open science.