add t5dst, multiwoz21: jga 53.2, slot f1 92.0

convlab2/base_models/t5/dst/run_dst.sh

+n_gpus=1
+task_name="dst"
+dataset_name=$1
+speaker="user"
+context_window_size=100
+data_dir="data/${task_name}/${dataset_name}/${speaker}/context_${context_window_size}"
+output_dir="output/${task_name}/${dataset_name}/${speaker}/context_${context_window_size}"
+cache_dir="../cache"
+logging_dir="${output_dir}/runs"
+train_file="${data_dir}/train.json"
+validation_file="${data_dir}/validation.json"
+test_file="${data_dir}/test.json"
+metric_name_or_path="dst_metric.py"
+metric_for_best_model="accuracy"
+source_column="context"
+target_column="state_seq"
+truncation_side="left"
+max_source_length=1024
+max_target_length=512
+model_name_or_path="t5-small"
+per_device_train_batch_size=64
+per_device_eval_batch_size=64
+gradient_accumulation_steps=2
+lr=1e-3
+num_train_epochs=10
+
+python ../create_data.py -t ${task_name} -d ${dataset_name} -s ${speaker} -c ${context_window_size} -l t5-small
+
+python -m torch.distributed.launch \
+    --nproc_per_node ${n_gpus} ../run_seq2seq.py \
+    --task_name ${task_name} \
+    --train_file ${train_file} \
+    --validation_file ${validation_file} \
+    --test_file ${test_file} \
+    --source_column ${source_column} \
+    --target_column ${target_column} \
+    --max_source_length ${max_source_length} \
+    --max_target_length ${max_target_length} \
+    --truncation_side ${truncation_side} \
+    --model_name_or_path ${model_name_or_path} \
+    --do_train \
+    --do_eval \
+    --do_predict \
+    --save_strategy epoch \
+    --evaluation_strategy epoch \
+    --prediction_loss_only \
+    --cache_dir ${cache_dir} \
+    --output_dir ${output_dir} \
+    --logging_dir ${logging_dir} \
+    --overwrite_output_dir \
+    --preprocessing_num_workers 4 \
+    --per_device_train_batch_size ${per_device_train_batch_size} \
+    --per_device_eval_batch_size ${per_device_eval_batch_size} \
+    --gradient_accumulation_steps ${gradient_accumulation_steps} \
+    --learning_rate ${lr} \
+    --num_train_epochs ${num_train_epochs} \
+    --debug underflow_overflow \
+    --adafactor \
+    --gradient_checkpointing
+
+python -m torch.distributed.launch \
+    --nproc_per_node ${n_gpus} ../run_seq2seq.py \
+    --task_name ${task_name} \
+    --test_file ${test_file} \
+    --source_column ${source_column} \
+    --target_column ${target_column} \
+    --max_source_length ${max_source_length} \
+    --max_target_length ${max_target_length} \
+    --truncation_side ${truncation_side} \
+    --model_name_or_path ${output_dir} \
+    --do_predict \
+    --predict_with_generate \
+    --metric_name_or_path ${metric_name_or_path} \
+    --cache_dir ${cache_dir} \
+    --output_dir ${output_dir} \
+    --logging_dir ${logging_dir} \
+    --overwrite_output_dir \
+    --preprocessing_num_workers 4 \
+    --per_device_eval_batch_size ${per_device_eval_batch_size}
+
+python merge_predict_res.py -d ${dataset_name} -s ${speaker} -c ${context_window_size} -p ${output_dir}/generated_predictions.json
+
+python ../../../dst/evaluate_unified_datasets.py -p ${output_dir}/predictions.json