import tensorflow as tf


		elif mode == tf.estimator.ModeKeys.EVAL:
			def metric_fn(per_example_loss,
						logits, 
						label_ids):
				"""Computes the loss and accuracy of the model."""
				sentence_log_probs = tf.reshape(
					logits, [-1, logits.shape[-1]])
				sentence_predictions = tf.argmax(
					logits, axis=-1, output_type=tf.int32)
				sentence_labels = tf.reshape(label_ids, [-1])
				sentence_accuracy = tf.metrics.accuracy(
					labels=label_ids, predictions=sentence_predictions)
				sentence_mean_loss = tf.metrics.mean(
					values=per_example_loss)
				sentence_f = tf_metrics.f1(label_ids, 
										sentence_predictions, 
										num_labels, 
										label_lst, average="macro")

				eval_metric_ops = {
									"f1": sentence_f,
