2024-10-27 20:28:57 +08:00

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# the instruction and training config version
version="llm-embedder"
# the output folder
output="llm-embedder"
# the data root where you untar the data
data_root="/data/llm-embedder"
torchrun --nproc_per_node=8 run_dense.py --train_data \
llm-embedder:chat/msc/train.json \
llm-embedder:convsearch/qrecc/train.concat.json \
llm-embedder:lrlm/arxiv/train.json \
llm-embedder:lrlm/books3/train.json \
llm-embedder:lrlm/codeparrot/train.json \
llm-embedder:qa/msmarco/train.json \
llm-embedder:qa/nq/train.json \
llm-embedder:tool/toolbench/train.json \
llm-embedder:tool/toolbench/train.json \
llm-embedder:icl/icl/train.json \
--output_dir data/outputs/$output \
--save_steps 10000 \
--max_steps 10000 \
--logging_steps 100 \
--inbatch_same_dataset epoch \
--use_train_config \
--gradient_checkpointing \
--per_device_train_batch_size 100 \
--deepspeed data/deepspeed/stage0.json \
--version $version \
--learning_rate 5e-6 \
--data_root $data_root
for model in "checkpoint-10000"
do
torchrun --nproc_per_node 8 -m evaluation.eval_mmlu --query_encoder data/outputs/$output/$model/encoder --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_popqa --query_encoder data/outputs/$output/$model/encoder --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_msc --query_encoder data/outputs/$output/$model/encoder --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_tool --query_encoder data/outputs/$output/$model/encoder --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_lrlm --query_encoder data/outputs/$output/$model/encoder --eval_data llm-embedder:lrlm/books3/test.json --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_lrlm --query_encoder data/outputs/$output/$model/encoder --eval_data llm-embedder:lrlm/arxiv/test.json --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_lrlm --query_encoder data/outputs/$output/$model/encoder --eval_data llm-embedder:lrlm/codeparrot/test.json --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_lrlm --query_encoder data/outputs/$output/$model/encoder --eval_data llm-embedder:lrlm/pg19/test.json --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_icl --query_encoder data/outputs/$output/$model/encoder --version $version --data_root $data_root
torchrun --nproc_per_node 8 -m evaluation.eval_qrecc --query_encoder data/outputs/$output/$model/encoder --version $version --data_root $data_root
done