[debug] fix config format

qwen3_0.6b+qwen3_4b_base_Fuser/config.json

@@ -1,82 +1,60 @@
-model:
-  base_model: "Qwen/Qwen3-0.6B"
-  teacher_model: "Qwen/Qwen3-4B-Base"
-  include_response: false
-  is_do_alignment: false
-  alignment_strategy: "first"
-  projector:
-    type: "C2CProjector"
-    params:
-      hidden_dim: 1024
-      intermediate_dim: 1024
-      num_layers: 3
-      dropout: 0.1
-      initial_temperature: 1.0
-      final_temperature: 0.001
-      anneal_steps: 1953
-  # projector:
-  #   type: "AllInOneProjector"
-  #   params:
-  #     hidden_dim: 1024
-  #     weight_hidden_dim: 1024
-  #     num_layers: 3
-  #     dropout: 0.1
-  #     activation: "gelu"
-  #     use_layer_norm: true
-  #     use_residual: true
-  #     use_swiglu: true
-  #     use_concat: true
-  #     gate_granularity: "scalar"
-  #     gate_depends_on_input: false
-  #     gate_input_features: "target_key"
-  #     gate_init_value: 0.0
-  #     weight_granularity: "head_merged"
-  #     weight_depends_on_input: true
-  #     weight_input_features: "target_projected_key"
-  #     weight_init_value: 0.0
-  #     use_gumbel: true
-  #     initial_temperature: 1.0
-  #     final_temperature: 0.001
-  #     preserve_target_weight: false
-  #     add_self: true
-  #     anneal_steps: 1929
-  #     scalar_temperature: 1.0
-  #     max_sequence_length: 8192
-  mapping: "last_aligned"
-
-training:
-  learning_rate: 0.0001
-  weight_decay: 0.01
-  num_epochs: 1
-  max_length: 2048
-  device: "cuda"
-  scheduler_type: "linear"
-  warmup_ratio: 0.1
-  max_grad_norm: 1.0
-  gradient_accumulation_steps: 4
-  per_device_train_batch_size: 8
-  num_processes: 8
-  freeze:
-    - "teacher"
-    - "base"
-  seed: 42
-
-output:
-  output_dir: "local/checkpoints/Q3-0.6B_Q3-4B-Base_general_500k_C2C"
-  save_steps: 500
-  eval_steps: 100
-  wandb_config:
-    project: "Rosetta"
-    mode: "online"
-    entity: "nics-efc"
-    run_name: "Q3-0.6B_Q3-4B-Base_general_500k_C2C"
-
-data:
-  type: "OpenHermesChatDataset"
-  # type: "DollyChatDataset"
-
-  kwargs:
-    split: "train"
-    max_word_count: 2048
-    num_samples: 500000
-  train_ratio: 0.99
+{
+  "model": {
+    "base_model": "Qwen/Qwen3-0.6B",
+    "teacher_model": "Qwen/Qwen3-4B-Base",
+    "include_response": false,
+    "is_do_alignment": false,
+    "alignment_strategy": "first",
+    "projector": {
+      "type": "C2CProjector",
+      "params": {
+        "hidden_dim": 1024,
+        "intermediate_dim": 1024,
+        "num_layers": 3,
+        "dropout": 0.1,
+        "initial_temperature": 1.0,
+        "final_temperature": 0.001,
+        "anneal_steps": 1953
+      }
+    },
+    "mapping": "last_aligned"
+  },
+  "training": {
+    "learning_rate": 0.0001,
+    "weight_decay": 0.01,
+    "num_epochs": 1,
+    "max_length": 2048,
+    "device": "cuda",
+    "scheduler_type": "linear",
+    "warmup_ratio": 0.1,
+    "max_grad_norm": 1.0,
+    "gradient_accumulation_steps": 4,
+    "per_device_train_batch_size": 8,
+    "num_processes": 8,
+    "freeze": [
+      "teacher",
+      "base"
+    ],
+    "seed": 42
+  },
+  "output": {
+    "output_dir": "local/checkpoints/Q3-0.6B_Q3-4B-Base_general_500k_C2C",
+    "save_steps": 500,
+    "eval_steps": 100,
+    "wandb_config": {
+      "project": "Rosetta",
+      "mode": "online",
+      "entity": "nics-efc",
+      "run_name": "Q3-0.6B_Q3-4B-Base_general_500k_C2C"
+    }
+  },
+  "data": {
+    "type": "OpenHermesChatDataset",
+    "kwargs": {
+      "split": "train",
+      "max_word_count": 2048,
+      "num_samples": 500000
+    },
+    "train_ratio": 0.99
+  }
+}