support report custom args

Former-commit-id: d41254c40a1c5cacf9377096adb27efa9bdb79ea

src/llamafactory/hparams/data_args.py

@@ -15,8 +15,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from dataclasses import dataclass, field
-from typing import Literal, Optional
+from dataclasses import asdict, dataclass, field
+from typing import Any, Dict, Literal, Optional
 
 
 @dataclass
@@ -161,3 +161,6 @@ class DataArguments:
 
         if self.mask_history and self.train_on_prompt:
             raise ValueError("`mask_history` is incompatible with `train_on_prompt`.")
+
+    def to_dict(self) -> Dict[str, Any]:
+        return asdict(self)

src/llamafactory/hparams/finetuning_args.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from dataclasses import dataclass, field
-from typing import List, Literal, Optional
+from dataclasses import asdict, dataclass, field
+from typing import Any, Dict, List, Literal, Optional
 
 
 @dataclass
@@ -318,7 +318,7 @@ class SwanLabArguments:
         default=None,
         metadata={"help": "The workspace name in SwanLab."},
     )
-    swanlab_experiment_name: str = field(
+    swanlab_run_name: str = field(
         default=None,
         metadata={"help": "The experiment name in SwanLab."},
     )
@@ -440,3 +440,8 @@ class FinetuningArguments(
 
             if self.pissa_init:
                 raise ValueError("`pissa_init` is only valid for LoRA training.")
+
+    def to_dict(self) -> Dict[str, Any]:
+        args = asdict(self)
+        args = {k: f"<{k.upper()}>" if k.endswith("api_key") else v for k, v in args.items()}
+        return args

src/llamafactory/hparams/model_args.py

@@ -16,7 +16,7 @@
 # limitations under the License.
 
 import json
-from dataclasses import dataclass, field, fields
+from dataclasses import asdict, dataclass, field, fields
 from typing import Any, Dict, Literal, Optional, Union
 
 import torch
@@ -344,3 +344,8 @@ class ModelArguments(QuantizationArguments, ProcessorArguments, ExportArguments,
             setattr(result, name, value)
 
         return result
+
+    def to_dict(self) -> Dict[str, Any]:
+        args = asdict(self)
+        args = {k: f"<{k.upper()}>" if k.endswith("token") else v for k, v in args.items()}
+        return args