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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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datasets:
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- tatsu-lab/alpaca
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---
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This repo contains a low-rank adapter for LLaMA-7b
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fit on the [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca) dataset.
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This version of the weights was trained with the following hyperparameters:
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- Epochs: 3 (load from best epoch)
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- Batch size: 32
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- Learning rate: 1e-4
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- Lora _r_: 8
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- lora_alpha : 16
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- Lora target modules: q_proj, v_proj
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That is:
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```
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python train_alpaca_lora.py \
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--model_name_or_path decapoda-research/llama-7b-hf \
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--data_path tatsu-lab/alpaca \
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--output_dir work_dir_lora/ \
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--num_train_epochs 3 \
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--per_device_train_batch_size 4 \
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--per_device_eval_batch_size 4 \
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--gradient_accumulation_steps 8 \
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--evaluation_strategy "no" \
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--save_strategy "steps" \
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--save_steps 500 \
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--save_total_limit 5 \
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--learning_rate 1e-4 \
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--weight_decay 0. \
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--warmup_ratio 0.03 \
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--lr_scheduler_type "cosine" \
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--model_max_length 2048 \
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--logging_steps 1 \
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--fp16 True
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```
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Instructions for running it can be found at https://github.com/jianzhnie/open-chatgpt.
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