Not able to pass validation set when I add events!

[NisarAhamad]

After adding events dataframe, I am not able to add validation set to validate how well my model is performing.

Ex: I have data from 2020-02-02 to 2023-01-13. I have divided the data into train and test. The date format is YYYY-MM-DD

Train : 2020-02-02 - 2022-01-29
Test : 2022-01-30 - 2023-01-13

I would like to train the model using train data and validate the model using test data and forecast by adding events.

here is the below sample code:

import holidays

us_holidays = holidays.US(years=[2020,2021,2022,2023,2024,2025])

# Create an empty list to store holiday dates
holiday_dates = []

# Iterate through the holidays and append the date to the list
for date, name in us_holidays.items():
    holiday_dates.append([name, date])

# Create a DataFrame from the list of holiday dates
df = pd.DataFrame(holiday_dates, columns=['event', 'ds'])
Christmas = df[df['event']=='Christmas Day']
Thanksgiving = df[df['event']=='Thanksgiving']
Labour = df[df['event']=='Labor Day']
Independence = df[df['event']=='Independence Day']

events_df = pd.concat((Christmas, Thanksgiving, Labour, Independence))
events_df

model = NeuralProphet(growth='linear',
                      weekly_seasonality=True,
                      yearly_seasonality=True,
                      daily_seasonality=False,
                      num_hidden_layers=3,
                      loss_func='MAE',
                      epochs=30,
                      batch_size=64
                      )

# set the model to expect these events
model.add_events(['Christmas Day', 'Thanksgiving', 'Labor Day', 'Independence Day'])

# create the data df with events
history_df = model.create_df_with_events(train_df, events_df)

# fit the model
metrics = model.fit(history_df, freq="D", validation_df = test_df)     ## This line will give me an error saying KeyError: 'Christmas Day'

Let if I am doing any mistake
Thanks in advance

[NisarAhamad]

@ourownstory do we have any suggestions for this please!