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run_sentiment_experiments.sh
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run_sentiment_experiments.sh
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#!/bin/bash
. activate xformer-multisource-domain-adaptation
. setenv.sh
run_name="(emnlp-sentiment)"
model_dir="wandb_local/emnlp_sentiment_experiments"
tags="emnlp sentiment experiments"
for i in 1000,1 1001,2 666,3 7,4 50,5; do IFS=","; set -- $i;
# 1) Basic
python emnlp_final_experiments/sentiment-analysis/train_basic.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "basic-distilbert-${2}" \
--model_dir ${model_dir}/basic_distilbert \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003
indices_dir=`ls -d -t ${model_dir}/basic_distilbert/*/ | head -1`
# 2) Adv-6
python emnlp_final_experiments/sentiment-analysis/train_basic_domain_adversarial.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-adversarial-6-${2}" \
--model_dir ${model_dir}/distilbert_adversarial_6 \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--supervision_layer 6 \
--indices_dir ${indices_dir}
# 3) Adv-3
python emnlp_final_experiments/sentiment-analysis/train_basic_domain_adversarial.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-adversarial-3-${2}" \
--model_dir ${model_dir}/distilbert_adversarial_3 \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--supervision_layer 3 \
--indices_dir ${indices_dir}
# 4) Independent-Avg
python emnlp_final_experiments/sentiment-analysis/train_multi_view_averaging_individuals.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-averaging-individuals-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_averaging_individuals \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--indices_dir ${indices_dir}
avg_model=`ls -d -t ${model_dir}/distilbert_ensemble_averaging_individuals/*/ | head -1`
# 5) Independent-Ft
python emnlp_final_experiments/sentiment-analysis/train_multi_view_selective_weighting.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 30 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-selective-attention-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_selective_attention \
--tags ${tags} \
--pretrained_model ${avg_model} \
--indices_dir ${indices_dir}
# 6) MoE-DC
python emnlp_final_experiments/sentiment-analysis/train_multi_view_domainclassifier_individuals.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-domainclassifier-individuals-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_domainclassifier_individuals \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--indices_dir ${indices_dir} \
--pretrained_model ${avg_model}
# 7) MoE-Avg
python emnlp_final_experiments/sentiment-analysis/train_multi_view.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-averaging-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_averaging \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--ensemble_basic \
--indices_dir ${indices_dir}
# 8) MoE-Att
python emnlp_final_experiments/sentiment-analysis/train_multi_view.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-attention-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_attention \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--indices_dir ${indices_dir}
# 9) MoE-Att-Adv-6
python emnlp_final_experiments/sentiment-analysis/train_multi_view_domain_adversarial.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-attention-adversarial-6-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_attention_adversarial_6 \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--supervision_layer 6 \
--indices_dir ${indices_dir}
# 10) MoE-Att-Adv-3
python emnlp_final_experiments/sentiment-analysis/train_multi_view_domain_adversarial.py \
--dataset_loc data/sentiment-dataset \
--train_pct 0.9 \
--n_gpu 1 \
--n_epochs 5 \
--domains books dvd electronics kitchen_\&_housewares \
--seed ${1} \
--run_name "distilbert-ensemble-attention-adversarial-3-${2}" \
--model_dir ${model_dir}/distilbert_ensemble_attention_adversarial_4 \
--tags ${tags} \
--batch_size 8 \
--lr 0.00003 \
--supervision_layer 3 \
--indices_dir ${indices_dir}
done