No response when training the model using SLURM

[morestart]

print info

Using 16bit Automatic Mixed Precision (AMP)
GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
HPU available: False, using: 0 HPUs
wandb: WARNING `resume` will be ignored since W&B syncing is set to `offline`. Starting a new run with run id 0ns1bdov.
wandb: Tracking run with wandb version 0.17.4
wandb: W&B syncing is set to `offline` in this directory.  
wandb: Run `wandb online` or set WANDB_MODE=online to enable cloud syncing.
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]
Loading `train_dataloader` to estimate number of stepping batches.
┏━━━┳━━━━━━━┳━━━━━━┳━━━━━━━━┳━━━━━━━┓
┃   ┃ Name  ┃ Type ┃ Params ┃ Mode  ┃
┡━━━╇━━━━━━━╇━━━━━━╇━━━━━━━━╇━━━━━━━┩
│ 0 │ model │ ViT │  229 M │ train │
└───┴───────┴──────┴────────┴───────┘
Trainable params: 229 M                                                         
Non-trainable params: 0                                                         
Total params: 229 M                                                             
Total estimated model params size (MB): 917                                     
Modules in train mode: 785                                                      
Modules in eval mode: 0                                                         
SLURM auto-requeueing enabled. Setting signal handlers.

After that, it remains the same with no changes.

this is my slurm config:

#!/bin/bash
#SBATCH -J TXModel
#SBATCH -p dzagexclu03
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=1
#SBATCH --gres=gpu:1
#SBATCH --mem=524288
#SBATCH --cpus-per-task=8
export SRUN_CPUS_PER_TASK=8

module load nvidia/cuda/12.1
source ~/miniconda3/bin/activate dl

srun python train.py --config base.yaml