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Gaëtan Caillaut
minibert-deft2018
Commits
51481bdc
Commit
51481bdc
authored
Mar 25, 2021
by
Gaëtan Caillaut
Browse files
dev in slurm scripts
parent
f17b25e6
Changes
14
Hide whitespace changes
Inline
Side-by-side
slurm_scripts/job.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t1/train.csv"
DEV
=
"data/cleaned/t1/dev.csv"
TEST
=
"data/cleaned/t1/test.csv"
TOKENIZER
=
"output/tokenizer.json"
OUT_DIR
=
"models/cleaned"
...
...
@@ -41,9 +42,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py mlm
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--checkpoint
${
CHECKPOINT
}
--logdir
${
TB_DIR
}
python train.py mlm
${
TRAIN
}
${
TEST
}
$
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--checkpoint
${
CHECKPOINT
}
--logdir
${
TB_DIR
}
else
python train.py mlm
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py mlm
${
TRAIN
}
${
TEST
}
$
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t1/train.csv"
DEV
=
"data/lemmatized/t1/dev.csv"
TEST
=
"data/lemmatized/t1/test.csv"
TOKENIZER
=
"output/tokenizer_lemmatized.json"
OUT_DIR
=
"models/lemmatized"
...
...
@@ -41,9 +42,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py mlm
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--checkpoint
${
CHECKPOINT
}
--logdir
${
TB_DIR
}
python train.py mlm
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--checkpoint
${
CHECKPOINT
}
--logdir
${
TB_DIR
}
else
python train.py mlm
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py mlm
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--bs
${
BS
}
--epochs
10
--attention
${
ATT
}
--position
${
POS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t1.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t1/train.csv"
DEV
=
"data/cleaned/t1/dev.csv"
TEST
=
"data/cleaned/t1/test.csv"
TOKENIZER
=
"output/tokenizer.json"
PRETRAINED_DIR
=
"models/cleaned"
...
...
@@ -43,9 +44,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T1_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t1
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
python train.py t1
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
else
python train.py t1
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t1
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t1_camembert.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t1/train.csv"
DEV
=
"data/cleaned/t1/dev.csv"
TEST
=
"data/cleaned/t1/test.csv"
TOKENIZER
=
"output/tokenizer.json"
...
...
@@ -36,4 +37,4 @@ export PYTHONPATH="/lium/raid01_b/gcaillaut/polysemy/minibert:${PYTHONPATH}"
set
-x
set
-e
python train.py camembert-t1
${
TRAIN
}
${
TEST
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
python train.py camembert-t1
${
TRAIN
}
${
TEST
}
${
DEV
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
slurm_scripts/job_t1_camembert_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t1/train.csv"
DEV
=
"data/lemmatized/t1/dev.csv"
TEST
=
"data/lemmatized/t1/test.csv"
TOKENIZER
=
"output/tokenizer.json"
...
...
@@ -36,4 +37,4 @@ export PYTHONPATH="/lium/raid01_b/gcaillaut/polysemy/minibert:${PYTHONPATH}"
set
-x
set
-e
python train.py camembert-t1
${
TRAIN
}
${
TEST
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
python train.py camembert-t1
${
TRAIN
}
${
TEST
}
${
DEV
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
slurm_scripts/job_t1_fs.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t1/train.csv"
DEV
=
"data/cleaned/t1/dev.csv"
TEST
=
"data/cleaned/t1/test.csv"
TOKENIZER
=
"output/tokenizer.json"
PRETRAINED_DIR
=
"models/cleaned"
...
...
@@ -44,9 +45,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T1_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
else
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t1_fs_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t1/train.csv"
DEV
=
"data/lemmatized/t1/dev.csv"
TEST
=
"data/lemmatized/t1/test.csv"
TOKENIZER
=
"output/tokenizer_lemmatized.json"
PRETRAINED_DIR
=
"models/lemmatized"
...
...
@@ -44,9 +45,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T1_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
else
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t1-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t1_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t1/train.csv"
DEV
=
"data/lemmatized/t1/dev.csv"
TEST
=
"data/lemmatized/t1/test.csv"
TOKENIZER
=
"output/tokenizer_lemmatized.json"
PRETRAINED_DIR
=
"models/lemmatized"
...
...
@@ -43,11 +44,11 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T1_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t1
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/mi
\
python train.py t1
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/mi
\
nibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoi
\
nt
${
CHECKPOINT
}
else
python train.py t1
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/mi
\
python train.py t1
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/mi
\
nibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
...
...
slurm_scripts/job_t2.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t2/train.csv"
DEV
=
"data/cleaned/t2/dev.csv"
TEST
=
"data/cleaned/t2/test.csv"
TOKENIZER
=
"output/tokenizer.json"
PRETRAINED_DIR
=
"models/cleaned"
...
...
@@ -43,9 +44,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T2_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t2
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
python train.py t2
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
else
python train.py t2
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t2
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t2_camembert.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t2/train.csv"
DEV
=
"data/cleaned/t2/dev.csv"
TEST
=
"data/cleaned/t2/test.csv"
TOKENIZER
=
"output/tokenizer.json"
...
...
@@ -36,4 +37,4 @@ export PYTHONPATH="/lium/raid01_b/gcaillaut/polysemy/minibert:${PYTHONPATH}"
set
-x
set
-e
python train.py camembert-t2
${
TRAIN
}
${
TEST
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
python train.py camembert-t2
${
TRAIN
}
${
TEST
}
${
DEV
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
slurm_scripts/job_t2_camembert_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t2/train.csv"
DEV
=
"data/lemmatized/t2/dev.csv"
TEST
=
"data/lemmatized/t2/test.csv"
TOKENIZER
=
"output/tokenizer.json"
...
...
@@ -36,4 +37,4 @@ export PYTHONPATH="/lium/raid01_b/gcaillaut/polysemy/minibert:${PYTHONPATH}"
set
-x
set
-e
python train.py camembert-t2
${
TRAIN
}
${
TEST
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
python train.py camembert-t2
${
TRAIN
}
${
TEST
}
${
DEV
}
--outdir
${
OUT_DIR
}
--bs
${
BS
}
-e
100
--logdir
${
LOGDIR
}
--device
${
DEVICE
}
slurm_scripts/job_t2_fs.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/cleaned/t2/train.csv"
DEV
=
"data/cleaned/t2/dev.csv"
TEST
=
"data/cleaned/t2/test.csv"
TOKENIZER
=
"output/tokenizer.json"
PRETRAINED_DIR
=
"models/cleaned"
...
...
@@ -44,9 +45,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T2_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
else
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t2_fs_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t2/train.csv"
DEV
=
"data/lemmatized/t2/dev.csv"
TEST
=
"data/lemmatized/t2/test.csv"
TOKENIZER
=
"output/tokenizer_lemmatized.json"
PRETRAINED_DIR
=
"models/lemmatized"
...
...
@@ -44,9 +45,9 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T2_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoint
${
CHECKPOINT
}
else
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t2-fs
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
slurm_scripts/job_t2_lemmatized.sh
View file @
51481bdc
...
...
@@ -14,6 +14,7 @@ eval "$(conda shell.bash hook)"
conda activate polysemy
TRAIN
=
"data/lemmatized/t2/train.csv"
DEV
=
"data/lemmatized/t2/dev.csv"
TEST
=
"data/lemmatized/t2/test.csv"
TOKENIZER
=
"output/tokenizer_lemmatized.json"
PRETRAINED_DIR
=
"models/lemmatized"
...
...
@@ -43,10 +44,10 @@ for E in $(seq -f "%05g" 0 10 90); do
if
((
10#
$E
>
0
))
;
then
CHECKPOINT
=
"
${
OUT_DIR
}
/
${
T2_RUN_NAME
}
/checkpoint-
${
E
}
.tar"
python train.py t2
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoi
\
python train.py t2
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
--checkpoi
\
nt
${
CHECKPOINT
}
else
python train.py t2
${
TRAIN
}
${
TEST
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
python train.py t2
${
TRAIN
}
${
TEST
}
${
DEV
}
${
TOKENIZER
}
"
${
PRETRAINED_DIR
}
/
${
MLM_RUN_NAME
}
/minibert-model.pt"
-o
${
OUT_DIR
}
-d
${
D
}
--attention
${
ATT
}
--position
${
POS
}
--epochs
10
--bs
${
BS
}
--device
${
DEVICE
}
--logdir
${
TB_DIR
}
fi
done
done
...
...
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