chore: import upstream snapshot with attribution

2026-07-13 13:24:13 +08:00
commit 1037506f2e
6050 changed files with 1731598 additions and 0 deletions
@@ -0,0 +1,53 @@
+#!/usr/bin/env bash
+
+set -x
+set -e
+
+DIR="$( cd "$( dirname "$0" )" && cd .. && pwd )"
+echo "working directory: ${DIR}"
+
+if [ -z "$OUTPUT_DIR" ]; then
+  OUTPUT_DIR="${DIR}/checkpoint/kd_$(date +%F-%H%M.%S)"
+fi
+if [ -z "$DATA_DIR" ]; then
+  DATA_DIR="${DIR}/data/msmarco_distillation/"
+fi
+
+mkdir -p "${OUTPUT_DIR}"
+
+PROC_PER_NODE=$(nvidia-smi --list-gpus | wc -l)
+# python -u -m torch.distributed.launch --nproc_per_node ${PROC_PER_NODE} src/train_biencoder.py \
+deepspeed src/train_biencoder.py --deepspeed ds_config.json \
+    --model_name_or_path intfloat/simlm-base-msmarco \
+    --per_device_train_batch_size 16 \
+    --per_device_eval_batch_size 16 \
+    --kd_mask_hn False \
+    --kd_cont_loss_weight 0.2 \
+    --seed 123 \
+    --do_train \
+    --do_kd_biencoder \
+    --t 0.02 \
+    --fp16 \
+    --train_file "${DATA_DIR}/kd_train.jsonl" \
+    --validation_file "${DATA_DIR}/kd_dev.jsonl" \
+    --q_max_len 32 \
+    --p_max_len 144 \
+    --train_n_passages 24 \
+    --dataloader_num_workers 1 \
+    --num_train_epochs 6 \
+    --learning_rate 3e-5 \
+    --warmup_steps 1000 \
+    --share_encoder True \
+    --logging_steps 50 \
+    --output_dir "${OUTPUT_DIR}" \
+    --data_dir "${DATA_DIR}" \
+    --save_total_limit 10 \
+    --save_strategy epoch \
+    --evaluation_strategy epoch \
+    --load_best_model_at_end \
+    --metric_for_best_model mrr \
+    --greater_is_better True \
+    --remove_unused_columns False \
+    --overwrite_output_dir \
+    --disable_tqdm True \
+    --report_to none "$@"