metadata
license: mit
datasets:
- yahma/alpaca-cleaned
This repo contains a low-rank adapter for LLaMA-7b fit on the Stanford Alpaca dataset.
This version of the weights was trained with the following hyperparameters:
- Epochs: 10 (load from best epoch)
- Batch size: 128
- Cutoff length: 512
- Learning rate: 3e-4
- Lora r: 16
- Lora target modules: q_proj, k_proj, v_proj, o_proj
That is:
python finetune.py \
--base_model='decapoda-research/llama-7b-hf' \
--num_epochs=10 \
--cutoff_len=512 \
--group_by_length \
--output_dir='./lora-alpaca-512-qkvo' \
--lora_target_modules='[q_proj,k_proj,v_proj,o_proj]' \
--lora_r=16 \
--micro_batch_size=8
Instructions for running it can be found at https://github.com/tloen/alpaca-lora.