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run_joint.sh
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### 1. For Ji split, change the dataset to pdtb2 or pdtb3
# 2
<<"COMMENT"
python3 train_joint_conn_rel.py --do_train \
--dataset="other2" \
--label_file="labels_level_1.txt" \
--sample_k=100
COMMENT
# 9
# 11
# <<"COMMENT"
for seed in 106524 106464 106537 219539 430683
do
python3 train_joint_conn_rel.py --do_train \
--dataset="pdtb2" \
--label_file="labels_level_1.txt" \
--sample_k=100 \
--seed=${seed}
done
# COMMENT
# 22
sleep 10s
# 26
# <<"COMMENT"
for seed in 106524 106464 106537 219539 430683
do
python3 train_joint_conn_rel.py --do_train \
--dataset="pdtb2" \
--label_file="labels_level_2.txt" \
--sample_k=100 \
--seed=${seed}
done
# COMMENT
# 37
sleep 10s
### 2. For xval, change the dataset to pdtb2 or pdtb3
# 42
# <<"COMMENT"
for idx in 1 2 3 4 5 6 7 8 9 10 11 12
do
python3 train_joint_conn_rel.py --do_train \
--dataset="pdtb2" \
--fold_id=${idx} \
--label_file="labels_level_1.txt" \
--sample_k=100
done
# COMMENT
# 53
sleep 10s
# 57
# <<"COMMENT"
for idx in 1 2 3 4 5 6 7 8 9 10 11 12
do
python3 train_joint_conn_rel.py --do_train \
--dataset="pdtb2" \
--fold_id=${idx} \
--label_file="labels_level_2.txt" \
--sample_k=100
done
# COMMENT
# 68