first commit

scripts/classification/TimesNet.sh

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+export CUDA_VISIBLE_DEVICES=3
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/EthanolConcentration/ \
+  --model_id EthanolConcentration \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 2 \
+  --batch_size 16 \
+  --d_model 16 \
+  --d_ff 32 \
+  --top_k 3 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/FaceDetection/ \
+  --model_id FaceDetection \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 2 \
+  --batch_size 16 \
+  --d_model 64 \
+  --d_ff 256 \
+  --top_k 3 \
+  --num_kernels 4 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python run.py \
+--task_name classification \
+--is_training 1 \
+--root_path ./dataset/Handwriting/ \
+--model_id Handwriting \
+--model TimesNet \
+--data UEA \
+--e_layers 2 \
+--batch_size 16 \
+--d_model 32 \
+--d_ff 64 \
+--top_k 3 \
+--des 'Exp' \
+--itr 1 \
+--learning_rate 0.001 \
+--train_epochs 30 \
+--patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/Heartbeat/ \
+  --model_id Heartbeat \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 3 \
+  --batch_size 16 \
+  --d_model 16 \
+  --d_ff 32 \
+  --top_k 1 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/JapaneseVowels/ \
+  --model_id JapaneseVowels \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 2 \
+  --batch_size 16 \
+  --d_model 16 \
+  --d_ff 32 \
+  --top_k 3 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 60 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/PEMS-SF/ \
+  --model_id PEMS-SF \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 6 \
+  --batch_size 16 \
+  --d_model 64 \
+  --d_ff 64 \
+  --top_k 3 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/SelfRegulationSCP1/ \
+  --model_id SelfRegulationSCP1 \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 3 \
+  --batch_size 16 \
+  --d_model 16 \
+  --d_ff 32 \
+  --top_k 3 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/SelfRegulationSCP2/ \
+  --model_id SelfRegulationSCP2 \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 3 \
+  --batch_size 16 \
+  --d_model 32 \
+  --d_ff 32 \
+  --top_k 3 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/SpokenArabicDigits/ \
+  --model_id SpokenArabicDigits \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 2 \
+  --batch_size 16 \
+  --d_model 32 \
+  --d_ff 32 \
+  --top_k 2 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10
+
+python -u run.py \
+  --task_name classification \
+  --is_training 1 \
+  --root_path ./dataset/UWaveGestureLibrary/ \
+  --model_id UWaveGestureLibrary \
+  --model TimesNet \
+  --data UEA \
+  --e_layers 2 \
+  --batch_size 16 \
+  --d_model 32 \
+  --d_ff 64 \
+  --top_k 3 \
+  --des 'Exp' \
+  --itr 1 \
+  --learning_rate 0.001 \
+  --train_epochs 30 \
+  --patience 10