Arnav Chavan

Results 10 comments of Arnav Chavan

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.