Do not log the generation config for each prediction step in TrainerSeq2Seq (#21385)

Do not log the generation config for each iteration

src/transformers/trainer_seq2seq.py

@@ -199,6 +199,11 @@ class Seq2SeqTrainer(Trainer):
             generation_inputs,
             **gen_kwargs,
         )
+        # Temporary hack to ensure the generation config is not initialized for each iteration of the evaluation loop
+        # TODO: remove this hack when the legacy code that initializes generation_config from a model config is
+        # removed in https://github.com/huggingface/transformers/blob/98d88b23f54e5a23e741833f1e973fdf600cc2c5/src/transformers/generation/utils.py#L1183
+        if self.model.generation_config._from_model_config:
+            self.model.generation_config._from_model_config = False
         # in case the batch is shorter than max length, the output should be padded
         if gen_kwargs.get("max_length") is not None and generated_tokens.shape[-1] < gen_kwargs["max_length"]:
             generated_tokens = self._pad_tensors_to_max_len(generated_tokens, gen_kwargs["max_length"])