delete finetune_knwl_gen.sh

tasks/knwl_dialo/scripts/finetune_knwl_gen.sh

-#!/bin/bash
-
-# Finetune a pretrained language model to generate the context-relevant knowledge
-# The input is the dialogue context, and output is the relevant knowledge
-# The size of the pretrained language model is 357M
-
-WORLD_SIZE=8
-
-DISTRIBUTED_ARGS="--nproc_per_node $WORLD_SIZE \
-                  --nnodes 1 \
-                  --node_rank 0 \
-                  --master_addr localhost \
-                  --master_port 6000"
-
-CHECKPOINT_PATH=<PATH_OF_THE_LANGUAGE_MODEL>
-OUTPUT_MODEL_PATH=<PATH_OF_THE_SAVED_MODEL>
-VOCAB_PATH=<PATH_OF_THE_VOCAB_FILE>
-MERGE_PATH=<PATH_OF_THE_MERGE_FILE>
-TRAIN_PATH=<PATH_OF_THE_TRAINING_DATASET>
-TEST_PATH=<PATH_OF_THE_TEST_DATASET>
-
-python -m torch.distributed.launch $DISTRIBUTED_ARGS ./tasks/main.py \
-        --num-layers 24 \
-        --hidden-size 1024 \
-        --num-attention-heads 16 \
-        --seq-length 2048 \
-        --max-position-embeddings 2048 \
-        --micro-batch-size 4 \
-        --global-batch-size 64 \
-        --train-samples 61000 \
-        --lr-decay-samples 50000 \
-        --lr-warmup-samples 5000 \
-        --lr 1.5e-5 \
-        --min-lr 1.0e-5 \
-        --lr-decay-style cosine \
-        --vocab-file ${VOCAB_PATH} \
-        --merge-file ${MERGE_PATH} \
-        --save-interval 10000 \
-        --save ${OUTPUT_MODEL_PATH} \
-        --pretrained-checkpoint ${CHECKPOINT_PATH} \
-        --weight-decay 0.1 \
-        --adam-beta2 0.95 \
-        --log-params-norm \
-        --log-num-zeros-in-grad \
-        --fp16 \
-        --DDP-impl torch \
-        --checkpoint-activations \
-        --epochs 4 \
-        --task KNWL-DIALO-FINETUNE \
-        --module knowledge \
-        --spec-toks [SEP],[CTRL],[PAD] \
-        --train-data ${TRAIN_PATH} \
-        --test-data ${TEST_PATH} \
-        --tokenizer-type GPT2BPETokenizer