allow report_to for multiple providers (#1647)

src/axolotl/core/trainer_builder.py

@@ -1212,11 +1212,14 @@ class HFCausalTrainerBuilder(TrainerBuilderBase):
         )
         training_arguments_kwargs["group_by_length"] = self.cfg.group_by_length
         training_arguments_kwargs["curriculum_sampling"] = self.cfg.curriculum_sampling
-        report_to = None
+        report_to = []
         if self.cfg.use_wandb:
-            report_to = "wandb"
+            report_to.append("wandb")
         if self.cfg.use_mlflow:
-            report_to = "mlflow"
+            report_to.append("mlflow")
+        if self.cfg.use_tensorboard:
+            report_to.append("tensorboard")
+
         training_arguments_kwargs["report_to"] = report_to
         training_arguments_kwargs["run_name"] = (
             self.cfg.wandb_name if self.cfg.use_wandb else None

src/axolotl/utils/config/models/input/v0_4_1/__init__.py

@@ -212,7 +212,7 @@ class LoraConfig(BaseModel):
     lora_target_modules: Optional[List[str]] = None
     lora_target_linear: Optional[bool] = None
     lora_modules_to_save: Optional[List[str]] = None
-    lora_dropout: Optional[float] = None
+    lora_dropout: Optional[float] = 0.0
     peft_layers_to_transform: Optional[List[int]] = None
     peft: Optional[PeftConfig] = None
     peft_use_dora: Optional[bool] = None
@@ -609,6 +609,7 @@ class AxolotlInputConfig(
     early_stopping_patience: Optional[int] = None
     load_best_model_at_end: Optional[bool] = False
     save_only_model: Optional[bool] = False
+    use_tensorboard: Optional[bool] = None
 
     neftune_noise_alpha: Optional[float] = None