Fix(cfg): Add validation for save_strategy and eval_strategy

src/axolotl/utils/config.py

@@ -296,6 +296,24 @@ def validate_config(cfg):
                 cfg.datasets[idx].type = cfg.datasets[idx].type.replace(
                     "sharegpt_simple", "sharegpt"
                 )
+    if cfg.save_strategy and cfg.save_steps and cfg.save_strategy != "steps":
+        raise ValueError(
+            "save_strategy and save_steps mismatch. Please set save_strategy to 'steps' or remove save_steps."
+        )
+
+    if (
+        cfg.evaluation_strategy
+        and cfg.eval_steps
+        and cfg.evaluation_strategy != "steps"
+    ):
+        raise ValueError(
+            "evaluation_strategy and eval_steps mismatch. Please set evaluation_strategy to 'steps' or remove eval_steps."
+        )
+
+    if cfg.val_set_size == 0 and (cfg.eval_steps or cfg.evaluation_strategy):
+        raise ValueError(
+            "eval_steps and evaluation_strategy are not supported with val_set_size == 0"
+        )
 
     # TODO
     # MPT 7b

src/axolotl/utils/trainer.py

@@ -604,26 +604,19 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer, total_num_
             "sample_packing_efficiency"
         ] = cfg.sample_packing_eff_est
 
-    if cfg.eval_steps and cfg.evaluation_strategy:
-        # assume if the user set both, they know what they're doing
-        training_arguments_kwargs["evaluation_strategy"] = cfg.evaluation_strategy
+    if cfg.eval_steps:
+        training_arguments_kwargs["evaluation_strategy"] = "steps"
         training_arguments_kwargs["eval_steps"] = cfg.eval_steps
+    elif cfg.evaluation_strategy:
+        training_arguments_kwargs["evaluation_strategy"] = cfg.evaluation_strategy
     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 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
         training_arguments_kwargs["save_strategy"] = "steps"
         training_arguments_kwargs["save_steps"] = cfg.save_steps
     elif cfg.save_strategy:

tests/test_validation.py

@@ -397,3 +397,171 @@ def test_sharegpt_deprecation(self):
                 for record in self._caplog.records
             )
         assert cfg.datasets[0].type == "sharegpt:load_role"
+
+    def test_no_conflict_save_strategy(self):
+        cfg = DictDefault(
+            {
+                "save_strategy": "epoch",
+                "save_steps": 10,
+            }
+        )
+
+        with pytest.raises(
+            ValueError, match=r".*save_strategy and save_steps mismatch.*"
+        ):
+            validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "save_strategy": "no",
+                "save_steps": 10,
+            }
+        )
+
+        with pytest.raises(
+            ValueError, match=r".*save_strategy and save_steps mismatch.*"
+        ):
+            validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "save_strategy": "steps",
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "save_strategy": "steps",
+                "save_steps": 10,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "save_steps": 10,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "save_strategy": "no",
+            }
+        )
+
+        validate_config(cfg)
+
+    def test_no_conflict_eval_strategy(self):
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "epoch",
+                "eval_steps": 10,
+            }
+        )
+
+        with pytest.raises(
+            ValueError, match=r".*evaluation_strategy and eval_steps mismatch.*"
+        ):
+            validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "no",
+                "eval_steps": 10,
+            }
+        )
+
+        with pytest.raises(
+            ValueError, match=r".*evaluation_strategy and eval_steps mismatch.*"
+        ):
+            validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "steps",
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "steps",
+                "eval_steps": 10,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "eval_steps": 10,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "no",
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "epoch",
+                "val_set_size": 0,
+            }
+        )
+
+        with pytest.raises(
+            ValueError,
+            match=r".*eval_steps and evaluation_strategy are not supported with val_set_size == 0.*",
+        ):
+            validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "eval_steps": 10,
+                "val_set_size": 0,
+            }
+        )
+
+        with pytest.raises(
+            ValueError,
+            match=r".*eval_steps and evaluation_strategy are not supported with val_set_size == 0.*",
+        ):
+            validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "val_set_size": 0,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "eval_steps": 10,
+                "val_set_size": 0.01,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "evaluation_strategy": "epoch",
+                "val_set_size": 0.01,
+            }
+        )
+
+        validate_config(cfg)