diff --git a/examples/seq2seq/distillation.py b/examples/seq2seq/distillation.py
index 7dabb2b084f4ba..262fae182f50ca 100644
--- a/examples/seq2seq/distillation.py
+++ b/examples/seq2seq/distillation.py
@@ -262,7 +262,7 @@ class BartTranslationDistiller(BartSummarizationDistiller):
 
     mode = "translation"
     metric_names = ["bleu"]
-    default_val_metric = "bleu"
+    val_metric = "bleu"
 
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
diff --git a/examples/seq2seq/finetune.py b/examples/seq2seq/finetune.py
index cf47e32a4f2451..90591e1b0c0524 100644
--- a/examples/seq2seq/finetune.py
+++ b/examples/seq2seq/finetune.py
@@ -63,7 +63,7 @@ class SummarizationModule(BaseTransformer):
     mode = "summarization"
     loss_names = ["loss"]
     metric_names = ROUGE_KEYS
-    default_val_metric = "rouge2"
+    val_metric = "rouge2"
 
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, num_labels=None, mode=self.mode, **kwargs)
@@ -110,9 +110,6 @@ def __init__(self, hparams, **kwargs):
         self.dataset_class = (
             Seq2SeqDataset if hasattr(self.tokenizer, "prepare_seq2seq_batch") else LegacySeq2SeqDataset
         )
-        self.eval_beams = self.model.config.num_beams if self.hparams.eval_beams is None else self.hparams.eval_beams
-        assert self.eval_beams >= 1, f"got self.eval_beams={self.eval_beams}. Need an integer > 1"
-        self.val_metric = self.default_val_metric if self.hparams.val_metric is None else self.hparams.val_metric
 
     def freeze_embeds(self):
         """Freeze token embeddings and positional embeddings for bart, just token embeddings for t5."""
@@ -304,8 +301,6 @@ def add_model_specific_args(parser, root_dir):
         parser.add_argument("--label_smoothing", type=float, default=0.0, required=False)
         parser.add_argument("--src_lang", type=str, default="", required=False)
         parser.add_argument("--tgt_lang", type=str, default="", required=False)
-        parser.add_argument("--eval_beams", type=int, default=None, required=False)
-        parser.add_argument("--val_metric", type=str, default=None, required=False)
         parser.add_argument(
             "--early_stopping_patience",
             type=int,
@@ -320,7 +315,7 @@ class TranslationModule(SummarizationModule):
     mode = "translation"
     loss_names = ["loss"]
     metric_names = ["bleu"]
-    default_val_metric = "bleu"
+    val_metric = "bleu"
 
     def __init__(self, hparams, **kwargs):
         super().__init__(hparams, **kwargs)
diff --git a/examples/seq2seq/test_seq2seq_examples.py b/examples/seq2seq/test_seq2seq_examples.py
index 410c3ee0a4c7e5..e7c795b7c5d57e 100644
--- a/examples/seq2seq/test_seq2seq_examples.py
+++ b/examples/seq2seq/test_seq2seq_examples.py
@@ -31,8 +31,6 @@
 CUDA_AVAILABLE = torch.cuda.is_available()
 CHEAP_ARGS = {
     "label_smoothing": 0.2,
-    "eval_beams": 1,
-    "val_metric": None,
     "adafactor": True,
     "early_stopping_patience": 2,
     "logger_name": "default",