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export CUDA_VISIBLE_DEVICES=0
data_dir=${1:-"en-indic-exp"}
model_name=${2:-"ai4bharat/indictrans2-en-indic-dist-200M"}
output_dir=${3:-"output"}
src_lang_list=${4:-"eng_Latn"}
tgt_lang_list=${5:-"asm_Beng,ben_Beng,guj_Gujr,hin_Deva,kan_Knda,mal_Mlym,mar_Deva,npi_Deva,ory_Orya,pan_Guru,tam_Taml,tel_Telu,urd_Arab"}
python3 train_lora.py \
--data_dir $data_dir \
--model_name $model_name \
--output_dir $output_dir \
--src_lang_list $src_lang_list \
--tgt_lang_list $tgt_lang_list \
--save_steps 1000 \
--max_steps 1000000 \
--batch_size 32 \
--grad_accum_steps 4 \
--warmup_steps 4000 \
--max_grad_norm 1.0 \
--learning_rate 2e-4 \
--adam_beta1 0.9 \
--adam_beta2 0.98 \
--optimizer adamw_torch \
--lr_scheduler inverse_sqrt \
--num_workers 16 \
--metric_for_best_model eval_BLEU \
--greater_is_better \
--patience 10 \
--weight_decay 0.01 \
--lora_target_modules "q_proj,k_proj" \
--lora_dropout 0.1 \
--lora_r 16 \
--lora_alpha 32 \
--print_samples |