#!/bin/bash

source ~/.bashrc
conda activate agent_training

WANDB__SERVICE_WAIT=500 WANDB_PROJECT=agent WANDB_ENTITY=vl001 WANDB_NAME=popular_35-04~11_42-34_42-97_06-43_20-28_map_wikihow_0501_filtered_hover_role_train_33-16~27_39-99.nl_b32s23 deepspeed --hostfile hostfile --include babel-5-23:0,1,2,3 --master_port=9986 /home/bo/cais/deepseek_llamafactory/LLaMA-Factory/src/train_bash.py     --deepspeed ds_config_3_xofl.json     --stage sft     --model_name_or_path  /data/tir/projects/tir3/users/bo/ckpts/cllama/cllama/models--codellama--CodeLlama-7b-hf/snapshots/bc5283229e2fe411552f55c71657e97edf79066c     --do_train     --dataset popular_35-04~11_42-34_42-97_06-43_20-28_map_wikihow_0501_filtered_hover_role_train_33-16~27_39-99.nl     --train_size 28770     --shuffle False     --dataset_dir /home/bo/cais/agent/data/code/     --template llama2     --finetuning_type full     --output_dir /data/tir/projects/tir4/users/bo/ckpts/output_28k_popular_35-04~11_42-34_42-97_06-43_20-28_map_wikihow_0501_filtered_hover_role_train_33-16~27_39-99.nl_1e-5_b32s23/     --overwrite_output_dir True     --cache_path /scratch/bo/popular_35-04~11_42-34_42-97_06-43_20-28_map_wikihow_0501_filtered_hover_role_train_33-16~27_39-99.nl/     --per_device_train_batch_size 8     --per_device_eval_batch_size 1     --gradient_accumulation_steps 1     --gradient_checkpointing True     --lr_scheduler_type cosine     --evaluation_strategy "steps"     --save_strategy "steps"     --save_steps 500     --logging_steps "30"     --save_total_limit 5     --preprocessing_num_workers 16     --learning_rate 1e-5     --weight_decay 0.     --warmup_ratio 0.03     --num_train_epochs 5     --plot_loss     --bf16 True     --cutoff_len 4096     --report_to 'wandb'     --flash_attn True     --save_only_model     --seed 23

echo "exit code: $?"

    