### This is an example training of the task Handwriting

####SOFTMAX
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model transformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256  

##### ATTENTION-BN
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model normformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256 --weight_k 1.

##### ATTENTION-SH
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model shformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256 

#####ATTENTION-BN+SH
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model shformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256 --weight_k 1.

## LINEAR BASELINE AND LINEAR VERSIONS OF OUR METHOD
#### LINEAR
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model linearformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256 


##### ATTENTION-BN
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model linearformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256 --weight_k 1.


##### ATTENTION-SH
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model shlinformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256

#####ATTENTION-BN+SH
python src/main.py --output_dir experiments --comment "classification from Scratch" \
--records_file Classification_records.xls --data_dir /data/Multivariate_ts/Handwriting \
--output_dir /data/output_ts --data_class tsra --pattern TRAIN --val_pattern TEST \
--epochs 400 --lr 0.001 --optimizer RAdam --pos_encoding learnable  --task classification  \
--key_metric accuracy --model shlinformer --name Handwriting --dropout 0.1 --activation gelu \
--batch_size 128 --num_layers 1 --num_heads 8 --d_model 128 --dim_feedforward 256 --weight_k 1.