Merge pull request #215 from OpenAccess-AI-Collective/adamw-hyperparams-cfg

README.md

@@ -422,6 +422,12 @@ log_sweep_max_lr:
 optimizer:
 # specify weight decay
 weight_decay:
+# adamw hyperparams
+adam_beta1:
+adam_beta2:
+adam_epsilon:
+# Gradient clipping max norm
+max_grad_norm:
 
 # whether to bettertransformers
 flash_optimum:

src/axolotl/utils/trainer.py

@@ -115,6 +115,15 @@ def setup_trainer(cfg, train_dataset, eval_dataset, model, tokenizer):
             # TODO search Path("./") for one
             training_arguments_kwargs["deepspeed"] = "./ds_config.json"
 
+    if cfg.adam_beta1:
+        training_arguments_kwargs["adam_beta1"] = cfg.adam_beta1
+    if cfg.adam_beta2:
+        training_arguments_kwargs["adam_beta2"] = cfg.adam_beta2
+    if cfg.adam_epsilon:
+        training_arguments_kwargs["adam_epsilon"] = cfg.adam_epsilon
+    if cfg.max_grad_norm:
+        training_arguments_kwargs["max_grad_norm"] = cfg.max_grad_norm
+
     training_args = transformers.TrainingArguments(
         per_device_train_batch_size=cfg.micro_batch_size,
         per_device_eval_batch_size=cfg.eval_batch_size

src/axolotl/utils/validation.py

@@ -87,6 +87,11 @@ def validate_config(cfg):
             "You probably want to disable group_by_length as it will force a streamed dataset to download completely."
         )
 
+    if any([cfg.adamw_beta1, cfg.adamw_beta2, cfg.adamw_epsilon]) and (
+        not cfg.optimizer or "adamw" not in cfg.optimizer
+    ):
+        logging.warning("adamw hyperparameters found, but no adamw optimizer set")
+
     # TODO
     # MPT 7b
     # https://github.com/facebookresearch/bitsandbytes/issues/25

tests/test_validation.py

@@ -263,3 +263,53 @@ class ValidationTest(unittest.TestCase):
 
         with pytest.raises(ValueError, match=regex_exp):
             validate_config(cfg)
+
+    def test_adamw_hyperparams(self):
+        cfg = DictDefault(
+            {
+                "optimizer": None,
+                "adamw_epsilon": 0.0001,
+            }
+        )
+
+        with self._caplog.at_level(logging.WARNING):
+            validate_config(cfg)
+            assert any(
+                "adamw hyperparameters found, but no adamw optimizer set"
+                in record.message
+                for record in self._caplog.records
+            )
+
+        cfg = DictDefault(
+            {
+                "optimizer": "adafactor",
+                "adamw_beta1": 0.0001,
+            }
+        )
+
+        with self._caplog.at_level(logging.WARNING):
+            validate_config(cfg)
+            assert any(
+                "adamw hyperparameters found, but no adamw optimizer set"
+                in record.message
+                for record in self._caplog.records
+            )
+
+        cfg = DictDefault(
+            {
+                "optimizer": "adamw_bnb_8bit",
+                "adamw_beta1": 0.0001,
+                "adamw_beta2": 0.0001,
+                "adamw_epsilon": 0.0001,
+            }
+        )
+
+        validate_config(cfg)
+
+        cfg = DictDefault(
+            {
+                "optimizer": "adafactor",
+            }
+        )
+
+        validate_config(cfg)