Correct Year not displayed on matplotlib plot python

Question

So I am using LSTM model for multivariate time series prediction and plotting the predictions using matplotlib but it does not display accurate year which should be 2020 instead starts from 1970. My dataset is yarn market prices for china. Does anyone have any idea how I can fix it?

This is the code at the end for plotting

# ---> Special function: convert <datetime.date> to <Timestamp>
def datetime_to_timestamp(x):
    '''
        x : a given datetime value (datetime.date)
    '''
    return datetime.strptime(x.strftime('%Y%m%d'), '%Y%m%d')


y_pred_future = sc_predict.inverse_transform(predictions_future)
y_pred_train = sc_predict.inverse_transform(predictions_train)

PREDICTIONS_FUTURE = pd.DataFrame(y_pred_future, columns=['Cotton Yarn3']).set_index(pd.Series(datelist_future))
PREDICTION_TRAIN = pd.DataFrame(y_pred_train, columns=['Cotton Yarn3']).set_index(pd.Series(datelist_train[2 * n_past + n_future -1:]))

# Convert <datetime.date> to <Timestamp> for PREDCITION_TRAIN
PREDICTION_TRAIN.index = PREDICTION_TRAIN.index.to_series().apply(datetime_to_timestamp)

print(PREDICTION_TRAIN.head(3))
#plt.rcParams["figure.figsize"] = (20,3)
#rcParams['figure.figsize'] = 14, 5

# Plot parameters
START_DATE_FOR_PLOTTING = '2019-12-24'

plt.plot(PREDICTIONS_FUTURE.index, PREDICTIONS_FUTURE['Cotton Yarn3'], color='r', label='Predicted Stock Price')
plt.plot(PREDICTION_TRAIN.loc[START_DATE_FOR_PLOTTING:].index, PREDICTION_TRAIN.loc[START_DATE_FOR_PLOTTING:]['Cotton Yarn3'], color='orange', label='Training predictions')
plt.plot(dataset_train.loc[START_DATE_FOR_PLOTTING:].index, dataset_train.loc[START_DATE_FOR_PLOTTING:]['Cotton Yarn3'], color='b', label='Actual Stock Price')

plt.axvline(x = min(PREDICTIONS_FUTURE.index), color='green', linewidth=2, linestyle='--')

plt.grid(which='major', color='#cccccc', alpha=0.5)

plt.legend(shadow=True)
plt.title('Predcitions and Acutal Stock Prices', family='Arial', fontsize=12)
plt.xlabel('Timeline', family='Arial', fontsize=10)
plt.ylabel('Stock Price Value', family='Arial', fontsize=10)
plt.xticks(rotation=45, fontsize=8)
plt.show()
dataset_train = pd.DataFrame(dataset_train, columns=cols)
dataset_train.index = datelist_train
dataset_train.index = pd.to_datetime(dataset_train.index)

This is the CSV

Date    Cotton Yarn1    Cotton Yarn2    Cotton Yarn3    Cotton Yarn4    Cotton Yarn5
12/24/2019  20690   20568   100 122 101
12/25/2019  20660   20538   100 122 101
12/26/2019  20630   20518   100 112 101
12/27/2019  20630   20518   100 112 101
12/28/2019  20630   20518   100 112 101
12/29/2019  20635   20541   100 94  100
12/30/2019  20635   20541   100 94  100
12/31/2019  20700   20583   100 117 101
1/1/2020    20700   20583   100 117 101
1/2/2020    20710   20595   100 115 101
1/3/2020    20715   20604   100 111 101
1/4/2020    20715   20614   100 101 100
1/5/2020    20725   20623   100 102 100
1/6/2020    20725   20659   100 66  100
1/7/2020    20730   20673   101 57  100
1/8/2020    20730   20686   101 44  100
1/9/2020    20730   20686   101 44  100
1/10/2020   20730   20686   101 44  100
1/11/2020   20730   20686   101 44  100
1/12/2020   20730   20686   101 44  100
1/13/2020   20730   20686   101 44  100
1/14/2020   20730   20686   101 44  100
1/15/2020   20730   20686   101 44  100
1/16/2020   20730   20686   101 44  100
1/17/2020   20730   20686   101 44  100
1/18/2020   20730   20686   101 44  100
1/19/2020   20730   20686   101 44  100
1/20/2020   20730   20686   101 44  100
1/21/2020   20730   20686   101 44  100
1/22/2020   20530   20488   100 42  100
1/23/2020   20530   20488   100 42  100
1/24/2020   20530   20488   100 42  100
1/25/2020   20560   20518   100 42  100
1/26/2020   20560   20518   100 42  100
1/27/2020   20560   20518   100 42  100
1/28/2020   20560   20518   100 42  100
1/29/2020   20560   20518   100 42  100
1/30/2020   20560   20518   100 42  100
1/31/2020   20560   20518   100 42  100
2/1/2020    20580   20518   100 62  100
2/2/2020    20580   20518   100 62  100

Plot which is displayed