add --system-ids flag; add job_train_single.py for damped_spring

docs/plots/README.md

@@ -0,0 +1,16 @@
+# Training Curves
+
+PNGs in this directory are auto-generated by
+`physix.training.loop._render_training_curves` at end of every GRPO run, then
+mirrored from the HF model repo via `physix-train/sync-plots.sh`.
+
+Files:
+
+- `loss.png`              — GRPO surrogate loss over training steps.
+- `reward.png`            — Mean reward (with ±1σ band) over training steps.
+- `reward_components.png` — Per-component reward (`match`, `match_dense`,
+                             `correctness`, `simplicity`, `format`).
+
+To regenerate locally after a job:
+
+    ./physix-train/sync-plots.sh Pratyush-01/physix-3b-rl

physix/training/loop.py

@@ -99,6 +99,9 @@ class TrainingConfig(BaseModel):
     num_steps: int = 300
     seed: int = 0
     instances_per_system: int = 32
+    #: Subset of system IDs to train on. Defaults to all SUPPORTED_SYSTEMS.
+    #: Pass a single ID (e.g. ``("damped_spring",)``) for focused single-task runs.
+    system_ids: tuple[str, ...] = SUPPORTED_SYSTEMS
     ablation: Optional[Ablation] = None
     wandb_project: str = "physix-live"
     wandb_run_name: Optional[str] = None
@@ -535,7 +538,7 @@ def _build_and_format_dataset(
     tokenizer: AutoTokenizer,
 ) -> Dataset:
     spec = DatasetSpec(
-        system_ids=SUPPORTED_SYSTEMS,
+        system_ids=config.system_ids,
         instances_per_system=config.instances_per_system,
         seed=config.seed,
     )
@@ -543,8 +546,8 @@ def _build_and_format_dataset(
     _log.info(
         "Built training dataset: %d rows across %d systems (%s)",
         len(dataset),
-        len(SUPPORTED_SYSTEMS),
-        ", ".join(SUPPORTED_SYSTEMS),
+        len(config.system_ids),
+        ", ".join(config.system_ids),
     )
 
     def _apply_chat_template(example: dict[str, object]) -> dict[str, object]:
@@ -914,6 +917,15 @@ def _parse_args() -> TrainingConfig:
                         help="Max tokens per rollout completion. Shorter = faster generation.")
     parser.add_argument("--lora-r", type=int, default=16)
     parser.add_argument("--instances-per-system", type=int, default=32)
+    parser.add_argument(
+        "--system-ids",
+        default=None,
+        help=(
+            "Comma-separated list of system IDs to train on "
+            "(e.g. 'damped_spring' or 'free_fall,simple_pendulum'). "
+            "Defaults to all SUPPORTED_SYSTEMS when omitted."
+        ),
+    )
     parser.add_argument(
         "--ablation",
         choices=("no_progress", "no_simplicity", "no_format"),
@@ -961,6 +973,12 @@ def _parse_args() -> TrainingConfig:
             "--sft-checkpoint for a fresh GRPO from a merged SFT model."
         )
 
+    system_ids = (
+        tuple(s.strip() for s in args.system_ids.split(",") if s.strip())
+        if args.system_ids
+        else SUPPORTED_SYSTEMS
+    )
+
     return TrainingConfig(
         model_name=args.model,
         sft_checkpoint=args.sft_checkpoint,
@@ -972,6 +990,7 @@ def _parse_args() -> TrainingConfig:
         max_completion_length=args.max_completion_length,
         lora_r=args.lora_r,
         instances_per_system=args.instances_per_system,
+        system_ids=system_ids,
         ablation=args.ablation,
         save_method=args.save_method,
         wandb_project=args.wandb_project,

physix/training/sft.py

@@ -143,6 +143,7 @@ def train_sft(
     gradient_accumulation_steps: int = 4,
     learning_rate: float = 2e-5,
     instances_per_system: int = 32,
+    system_ids: tuple[str, ...] = SUPPORTED_SYSTEMS,
     seed: int = 0,
     wandb_run_name: str | None = None,
     hub_checkpoint_repo_id: str | None = None,
@@ -198,7 +199,7 @@ def train_sft(
         random_state=seed,
     )
 
-    dataset = build_sft_dataset(instances_per_system=instances_per_system, seed=seed)
+    dataset = build_sft_dataset(system_ids=system_ids, instances_per_system=instances_per_system, seed=seed)
 
     def _format_row(row: dict) -> dict:
         """Combine prompt + completion into a single training string."""
@@ -308,6 +309,14 @@ def main() -> None:
     parser.add_argument("--output-dir", default="runs/physix-1.5b-sft")
     parser.add_argument("--epochs", type=int, default=2)
     parser.add_argument("--instances-per-system", type=int, default=32)
+    parser.add_argument(
+        "--system-ids",
+        default=None,
+        help=(
+            "Comma-separated list of system IDs to include in the SFT dataset "
+            "(e.g. 'damped_spring'). Defaults to all SUPPORTED_SYSTEMS."
+        ),
+    )
     parser.add_argument("--lora-r", type=int, default=32)
     parser.add_argument("--learning-rate", type=float, default=2e-5)
     parser.add_argument("--seed", type=int, default=0)
@@ -323,6 +332,12 @@ def main() -> None:
     )
     args = parser.parse_args()
 
+    system_ids = (
+        tuple(s.strip() for s in args.system_ids.split(",") if s.strip())
+        if args.system_ids
+        else SUPPORTED_SYSTEMS
+    )
+
     os.environ.setdefault("WANDB_PROJECT", "physix-live")
     train_sft(
         model_name=args.model,
@@ -331,6 +346,7 @@ def main() -> None:
         lora_r=args.lora_r,
         learning_rate=args.learning_rate,
         instances_per_system=args.instances_per_system,
+        system_ids=system_ids,
         seed=args.seed,
         wandb_run_name=args.wandb_run_name,
         hub_checkpoint_repo_id=args.hub_checkpoint_repo_id,