README update

README.md

@@ -21,7 +21,7 @@ import numpy as np
 
 import tensorflow as tf
 from datasets import load_metric, Dataset, DatasetDict
-from transformers import TFAutoModel, TFAutoModelForSequenceClassification, AutoTokenizer, DataCollatorWithPadding, create_optimizer
+from transformers import TFAutoModelForSequenceClassification, AutoTokenizer, DataCollatorWithPadding, create_optimizer
 from transformers.keras_callbacks import KerasMetricCallback
 
 # This example shows how this model can be used:
@@ -88,7 +88,7 @@ tf_validation_dataset = encoded_dataset["val"].to_tf_dataset(
 )
 
 loss = tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True)
-num_epochs = 20
+num_epochs = 25
 batches_per_epoch = math.ceil(len(encoded_dataset["train"]) / batch_size)
 total_train_steps = int(batches_per_epoch * num_epochs)