Arnav Chavan
Arnav Chavan
I am also facing a similar issue!
Did you complete the implementation and were you able to reproduce the original results?
This is great, this opens up lit-llama based finetuned models to be published on the hugging face leaderboard!
Yes, but it should be pretty simpler I guess, I just have one concern - the time taken for evaluation seems to be higher than other huggingface models. Can you...
Any headsup on how I can implement higher batch sizes? I will try to implement it over the weekend! Update - It works directly just by hardcoding any batch size...
I tried both the variants - 1. Having pad token = eos token 2. Using L218 in run_dpo.py to add an explicit [PAD] token. In both the cases the issue...
I am using transformers 4.42.4 and trl 0.9.6. I tried using the DPOTrainer from TRL and still faced the same issue. @WeiXiongUST if you get time can you please try...
Thanks alot, any idea on the GPU hours you need for this run?
Thanks for your reply! Did you perform a zero-shot evaluation on the LoRA fine-tuned+pruned models? This is practically very important as models undergo fine-tuning before deployment.
Please let me know if you have the checkpoint someplace, would save some time for me. I am interested in seeing the role of peft in sparse models.