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README.md
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license: mit
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---
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license: mit
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datasets:
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- yahma/alpaca-cleaned
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This repo contains a low-rank adapter for LLaMA-13b fit on the Cleaned Alpaca dataset.
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This version of the weights was trained with the following hyperparameters:
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Cleaned dataset: Snapshot April 2, 2023
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Epochs: 3
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Validation set size: 2000
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Batch size: 128
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Micro batch size: 8
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Cutoff length: 512
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Learning rate: 3e-4
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Lora r: 16
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Lora target modules: q_proj, k_proj, v_proj, o_proj
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That is:
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python finetune.py \
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--base_model='decapoda-research/llama-13b-hf' \
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--data_path 'yahma/alpaca-cleaned' \
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--num_epochs=3 \
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--cutoff_len=512 \
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--output_dir='./lora-alpaca' \
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--lora_target_modules='[q_proj,k_proj, v_proj, o_proj]' \
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--lora_r=16 \
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--val_set_size 2000 \
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--micro_batch_size=8
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