better eval handling

src/axolotl/utils/trainer.py

@@ -563,13 +563,16 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
  elif cfg.val_set_size == 0:
  # no eval set, so don't eval
  training_arguments_kwargs["evaluation_strategy"] = "no"
- elif cfg.evaluation_strategy and cfg.evaluation_strategy == "epoch":
+ elif cfg.evaluation_strategy and cfg.evaluation_strategy in ["epoch", "no"]:
  # if explicitly set for epoch, just set, and eval steps don't matter
  training_arguments_kwargs["evaluation_strategy"] = cfg.evaluation_strategy
  elif cfg.eval_steps:
  # steps isn't used w/ epochs
  training_arguments_kwargs["evaluation_strategy"] = "steps"
  training_arguments_kwargs["eval_steps"] = cfg.eval_steps
+ else:
+ # we have an eval set, but no steps defined, default to use epoch
+ training_arguments_kwargs["evaluation_strategy"] = "epoch"
 
  if cfg.save_steps:
  # save_steps implies save_strategy of steps