Issue with Optuna visualization in web browser
Hello everyone,I am using the Optuna library for hyperparameter optimization in a language model training script. I am trying to visualize the optimization results using Optuna’splot_optimization_historyfunction and then saving the figure as an HTML file usingfig.write_html("optuna_visualization.html").The HTML file is successfully created and opens correctly in all browsers. However, the figure does not show any data. In the terminal, the best hyperparameters are printed correctly.Here is a snippet of my code:# Ask the user if they would like to use Optuna for hyperparameter optimization
        optuna_mode = input("\n➤Would you like to use the default or Optuna settings to train? (\033[94mpadrao\033[0m/\033[91moptuna\033[0m): ")
        print()
  
        study_name = "tess"
        db_path = "example.db"
        if optuna_mode.lower() == 'optuna':
            study = optuna.create_study(study_name=study_name, storage=f"sqlite:///{db_path}", direction="minimize")
            study.optimize(lambda trial: objective(trial, model, tokenized_datasets, data_collator, tokenizer), n_trials=2)

            if len([t for t in study.trials if t.state == optuna.trial.TrialState.COMPLETE]) > 0:
                best_params = study.best_params
                print("\nBest hyperparameters: ", best_params)
                # View the results
                fig = vis.plot_optimization_history(study)
                fig.write_html("optuna_visualization.html")
                fig.show()
            else:
                print("No attempts were completed.")And theobjectivefunction:# Function for hyperparameter optimization with Optuna
def objective(trial, model, tokenized_datasets, data_collator, tokenizer):
    learning_rate = trial.suggest_float("learning_rate", 1e-6, 1e-3, log=True)
    num_train_epochs = trial.suggest_int("num_train_epochs", 2, 4)
    weight_decay = trial.suggest_float("weight_decay", 1e-12, 1e-1, log=True)
    adam_epsilon = trial.suggest_float("adam_epsilon", 1e-10, 1e-6, log=True)
    per_device_train_batch_size = trial.suggest_categorical("per_device_train_batch_size", [8, 16, 32])

    print(f"\nHyperparameters Suggestion: learning_rate={learning_rate}, num_train_epochs={num_train_epochs}, weight_decay={weight_decay}, per_device_train_batch_size={per_device_train_batch_size}\n")

    training_args = TrainingArguments(
        output_dir=model_dir,
        overwrite_output_dir=True,
        num_train_epochs=num_train_epochs,
        per_device_train_batch_size=per_device_train_batch_size,
        learning_rate=learning_rate,
        weight_decay=weight_decay,
        adam_epsilon=adam_epsilon,
        save_steps=1_000,
        save_total_limit=2,
        prediction_loss_only=True,
        logging_steps=10,
        logging_dir='./logs',
    )

    trainer = Trainer(
        model=model,
        args=training_args,
        train_dataset=tokenized_datasets["train"],
        data_collator=data_collator,
        tokenizer=tokenizer,
    )

    #logging.getLogger("transformers.trainer").setLevel(logging.ERROR)

    # Train the model
    trainer.train()

    eval_loss = None
    if trainer.eval_dataset is not None:
        eval_loss = trainer.evaluate()["eval_loss"]
        print(f"Eval loss: {eval_loss}")

    return eval_loss if eval_loss is not None else float('inf')I have checked that thestudyobject contains the correct optimization results and that the visualization is being generated correctly. When I open the HTML file in the browser and check the developer console, I see no JavaScript errors.Has anyone encountered a similar issue or have any idea how I can resolve this?Thank you!