This repo contains a low-rank adapter for LLaMA-7b fit on the Cleaned Alpaca dataset (with the new GPT-4 training data).
This version of the weights was trained with the following hyperparameters:
Cleaned dataset: Snapshot April 8, 2023
Epochs: 6 (Checkpoint with lowest eval loss at 3.6 epochs uploaded here)
Validation set size: 1500
Batch size: 128
Micro batch size: 8
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='yahma/llama-7b-hf'
--data_path 'yahma/alpaca-cleaned'
--num_epochs=6
--cutoff_len=512
--output_dir='./lora-alpaca'
--lora_target_modules='[q_proj,k_proj, v_proj, o_proj]'
--lora_r=16
--val_set_size 1500
--micro_batch_size=8
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