# How to stop Optuna saving checkpoints during Hyperparameter Search

**URL:** <https://discuss.huggingface.co/t/how-to-stop-optuna-saving-checkpoints-during-hyperparameter-search/6785>\
**Category:** Beginners\
**Created:** [June 14, 2021, 8:00am UTC](https://discuss.huggingface.co/t/how-to-stop-optuna-saving-checkpoints-during-hyperparameter-search/6785 "2021-06-14T08:00:16Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![theudster](https://avatars.discourse-cdn.com/v4/letter/t/97f17d/32.png) [@theudster](https://discuss.huggingface.co/u/theudster)\
**Post date:** [June 14, 2021, 8:00am UTC](https://discuss.huggingface.co/t/how-to-stop-optuna-saving-checkpoints-during-hyperparameter-search/6785/1 "2021-06-14T08:00:16Z")

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Hello I am running a Hyperparameter search using Optuna.  
As I am using Colab, I have limited diskspace, so I was wondering how to stop saving checkpoints, I only care about the final result and don’t need all the intermediate steps saved.  
I tried the following argument sin my TrainingArguments parameter, but its not working

```auto
# Define the trainig arguments
training_args = TrainingArguments(
    output_dir='./results', # output directory
    seed = 0,
    num_train_epochs=5, # total number of training epochs
    per_device_train_batch_size=16, # batch size per device during training
    per_device_eval_batch_size=16, # batch size for evaluation
    warmup_steps=22, # number of warmup steps for learning rate scheduler
    weight_decay=0.01, # strength of weight decay
    learning_rate=5e-5, # initial learning rate for AdamW optimizer.           
    load_best_model_at_end=True, # load the best model when finished training (default metric is loss)
    do_train=True, # Perform training
    do_eval=True, # Perform evaluation
    logging_dir='./logs', # directory for storing logs    
    logging_steps=10,
    gradient_accumulation_steps=2, # total number of steps before back propagation
    fp16=True, # Use mixed precision
    fp16_opt_level="02", # mixed precision mode
    evaluation_strategy="epoch", # evaluate each `logging_steps`
    save_strategy = 'no', # The checkpoint save strategy to adopt during training. I dont want to save, probably why it did save and take up disk space in HP search
    save_steps = 100000,
    save_total_limit = 1. # Trying this to stop octuna from saving

```

Any help would be appreciated, thank you!

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<div class="post-metadata">

**Author:** ![theudster](https://avatars.discourse-cdn.com/v4/letter/t/97f17d/32.png) [@theudster](https://discuss.huggingface.co/u/theudster)\
**Post date:** [June 14, 2021, 10:45am UTC](https://discuss.huggingface.co/t/how-to-stop-optuna-saving-checkpoints-during-hyperparameter-search/6785/2 "2021-06-14T10:45:35Z")

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Ok after reading the documentation carefully, it turns out setting  
`load_best_model_at_end=True,` overrides the strategy. Took it off and now it works.