trainbart.sh error

[RifatUllah102]

I am trying to run trainbart.sh script. the script contains the following information:

`TOTAL_NUM_UPDATES=20000
WARMUP_UPDATES=500
LR=3e-05 MAX_TOKENS=1024 UPDATE_FREQ=16 BART_PATH=/home/mdrullah/MARMAID/fairseq/BERT_Large/bart.large/model.pt

python train.py metaphor
--restore-file $BART_PATH
--max-tokens $MAX_TOKENS
--task translation
--source-lang source --target-lang target
--truncate-source
--truncate-target
--layernorm-embedding
--share-all-embeddings
--share-decoder-input-output-embed
--reset-optimizer --reset-dataloader --reset-meters
--required-batch-size-multiple 1
--arch bart_large
--criterion fairseq.criterions.label_smoothed_cross_entropy
--label-smoothing 0.1
--dropout 0.1 --attention-dropout 0.1
--weight-decay 0.01 --optimizer adam --adam-betas "(0.9, 0.999)" --adam-eps 1e-08
--clip-norm 0.1
--lr-scheduler polynomial_decay --lr $LR --total-num-update $TOTAL_NUM_UPDATES --warmup-updates $WARMUP_UPDATES
--memory-efficient-fp16 --update-freq $UPDATE_FREQ
--save-dir "checkpoint-metaphor"
--ddp-backend=no_c10d
--skip-invalid-size-inputs-valid-test
--find-unused-parameters;`

and I am getting the following error: usage: train.py [-h] [--no-progress-bar] [--log-interval N] [--log-format {json,none,simple,tqdm}] [--tensorboard-logdir DIR] [--seed N] [--cpu] [--fp16] [--memory-efficient-fp16] [--fp16-no-flatten-grads] [--fp16-init-scale FP16_INIT_SCALE] [--fp16-scale-window FP16_SCALE_WINDOW] [--fp16-scale-tolerance FP16_SCALE_TOLERANCE] [--min-loss-scale D] [--threshold-loss-scale THRESHOLD_LOSS_SCALE] [--user-dir USER_DIR] [--empty-cache-freq EMPTY_CACHE_FREQ] [--all-gather-list-size ALL_GATHER_LIST_SIZE] [--tokenizer {space,moses,nltk}] [--bpe {subword_nmt,sentencepiece,bert,gpt2,fastbpe}] [--optimizer {lamb,sgd,adadelta,adafactor,nag,adagrad,adam,adamax}] [--lr-scheduler {polynomial_decay,fixed,inverse_sqrt,tri_stage,triangular,cosine,reduce_lr_on_plateau}] [--task TASK] [--num-workers N] [--skip-invalid-size-inputs-valid-test] [--max-tokens N] [--max-sentences N] [--required-batch-size-multiple N] [--dataset-impl FORMAT] [--train-subset SPLIT] [--valid-subset SPLIT] [--validate-interval N] [--fixed-validation-seed N] [--disable-validation] [--max-tokens-valid N] [--max-sentences-valid N] [--curriculum N] [--distributed-world-size N] [--distributed-rank DISTRIBUTED_RANK] [--distributed-backend DISTRIBUTED_BACKEND] [--distributed-init-method DISTRIBUTED_INIT_METHOD] [--distributed-port DISTRIBUTED_PORT] [--device-id DEVICE_ID] [--distributed-no-spawn] [--ddp-backend {c10d,no_c10d}] [--bucket-cap-mb MB] [--fix-batches-to-gpus] [--find-unused-parameters] [--fast-stat-sync] --arch ARCH [--max-epoch N] [--max-update N] [--clip-norm NORM] [--sentence-avg] [--update-freq N1,N2,...,N_K] [--lr LR_1,LR_2,...,LR_N] [--min-lr LR] [--use-bmuf] [--save-dir DIR] [--restore-file RESTORE_FILE] [--reset-dataloader] [--reset-lr-scheduler] [--reset-meters] [--reset-optimizer] [--optimizer-overrides DICT] [--save-interval N] [--save-interval-updates N] [--keep-interval-updates N] [--keep-last-epochs N] [--keep-best-checkpoints N] [--no-save] [--no-epoch-checkpoints] [--no-last-checkpoints] [--no-save-optimizer-state] [--best-checkpoint-metric BEST_CHECKPOINT_METRIC] [--maximize-best-checkpoint-metric] [--patience N] [--activation-fn {relu,gelu,gelu_fast,gelu_accurate,tanh,linear}] [--dropout D] [--attention-dropout D] [--activation-dropout D] [--encoder-embed-path STR] [--encoder-embed-dim N] [--encoder-ffn-embed-dim N] [--encoder-layers N] [--encoder-attention-heads N] [--encoder-normalize-before] [--encoder-learned-pos] [--decoder-embed-path STR] [--decoder-embed-dim N] [--decoder-ffn-embed-dim N] [--decoder-layers N] [--decoder-attention-heads N] [--decoder-learned-pos] [--decoder-normalize-before] [--share-decoder-input-output-embed] [--share-all-embeddings] [--no-token-positional-embeddings] [--adaptive-softmax-cutoff EXPR] [--adaptive-softmax-dropout D] [--no-cross-attention] [--cross-self-attention] [--layer-wise-attention] [--encoder-layerdrop D] [--decoder-layerdrop D] [--encoder-layers-to-keep ENCODER_LAYERS_TO_KEEP] [--decoder-layers-to-keep DECODER_LAYERS_TO_KEEP] [--layernorm-embedding] [--no-scale-embedding] [--pooler-dropout D] [--pooler-activation-fn {relu,gelu,gelu_fast,gelu_accurate,tanh,linear}] [--adam-betas B] [--adam-eps D] [--weight-decay WD] [--use-old-adam] [--force-anneal N] [--warmup-updates N] [--end-learning-rate END_LEARNING_RATE] [--power POWER] [--total-num-update TOTAL_NUM_UPDATE] [-s SRC] [-t TARGET] [--load-alignments] [--left-pad-source BOOL] [--left-pad-target BOOL] [--max-source-positions N] [--max-target-positions N] [--upsample-primary UPSAMPLE_PRIMARY] [--truncate-source] [--truncate-target] data **train.py: error: unrecognized arguments: --criterion fairseqcriterionslabel_smoothed_cross_entropy --label-smoothing 0.1**

I've tried to run trainbart.sh --criterion label_smoothed_cross_entropy without the path too, but showing the same error.

Can anyone help me with what's wrong with my script?