diff --git a/xtuner/v1/datasets/config.py b/xtuner/v1/datasets/config.py
index c81dc9d0d..b3cd12cc3 100644
--- a/xtuner/v1/datasets/config.py
+++ b/xtuner/v1/datasets/config.py
@@ -13,6 +13,7 @@
 from torch.distributed.device_mesh import DeviceMesh
 from torch.utils.data import ConcatDataset, RandomSampler, SequentialSampler
 from torch.utils.data import DataLoader as TorchDataLoader
+from tqdm import tqdm
 from typing_extensions import TypedDict
 
 from transformers import PreTrainedTokenizer, PreTrainedTokenizerFast
@@ -112,6 +113,9 @@ def build_datasets(
     if tokenizer_hash is None:
         tokenizer_hash = tokenizer_xxhash(tokenizer)[:16]
 
+    # Expand each dataset config into its concrete jsonl paths while keeping the
+    # owning config/tokenize_fn so multi-dataset setups don't share the wrong builder.
+    build_tasks: list[tuple[DatasetConfig, BaseTokenizeFnConfig, str | Path]] = []
     for config in dataset_config:
         _dataset_config = config["dataset"]
         assert isinstance(_dataset_config, DatasetConfig)
@@ -125,17 +129,24 @@ def build_datasets(
                 for f in list_dir_or_file(anno_path, suffix=".jsonl", list_dir=False, recursive=True)
             ]
         all_anno_path.sort()
-        for anno_path in all_anno_path:
-            _dataset_config = copy.deepcopy(_dataset_config)
-            _dataset_config.anno_path = anno_path
-            anno_name = os.path.basename(anno_path)  # for debug
-            _tokenize_fn = _tokenize_fn_name.build(tokenizer, tokenizer_hash=tokenizer_hash, anno_name=anno_name)
-            _dataset = _dataset_config.build(_tokenize_fn)
-            if get_rank() == 0:
-                logger.debug(
-                    f"[Dataset] (Original) {_dataset_config.name}/{os.path.basename(anno_path)}: {len(_dataset)} samples."
-                )
-            datasets.append(_dataset)
+        build_tasks.extend((_dataset_config, _tokenize_fn_name, path) for path in all_anno_path)
+
+    bar = None
+    if get_rank() == 0:
+        bar = tqdm(build_tasks, desc="Building datasets", unit="dataset")
+
+    for _dataset_config, _tokenize_fn_name, anno_path in build_tasks:
+        _dataset_config = copy.deepcopy(_dataset_config)
+        _dataset_config.anno_path = anno_path
+        anno_name = os.path.basename(anno_path)
+        _tokenize_fn = _tokenize_fn_name.build(tokenizer, tokenizer_hash=tokenizer_hash, anno_name=anno_name)
+        _dataset = _dataset_config.build(_tokenize_fn)
+        datasets.append(_dataset)
+
+        if get_rank() == 0:
+            assert bar is not None
+            bar.update(1)
+            bar.set_postfix_str(f"{Path(anno_path).stem} (cached: {_dataset.cached})")
 
     return datasets
 
@@ -154,7 +165,7 @@ def build_dataloader(
     dp_size = dp_mesh.size() if dp_mesh is not None else 1
     assert global_batch_size % dp_size == 0, "global_batch_size must be divisible by dp_size."
 
-    if dataloader_config.pack_level != "none" and get_rank == 0:
+    if dataloader_config.pack_level != "none" and get_rank() == 0:
         num_tokens = sum(dset.num_tokens.sum() for dset in datasets if dset.num_tokens is not None)
         logger.debug(f"[Dataset] {num_tokens} tokens.")
 
diff --git a/xtuner/v1/datasets/jsonl.py b/xtuner/v1/datasets/jsonl.py
index 96856e2fb..f6a5404a0 100644
--- a/xtuner/v1/datasets/jsonl.py
+++ b/xtuner/v1/datasets/jsonl.py
@@ -287,9 +287,11 @@ def __init__(
         logger.debug(f"[Dataset] Start loading [{self.name}]{self.path} with sample_ratio={sample_ratio}.")
 
         self._has_chunk = isinstance(tokenize_fn, LongTextPretrainTokenizeFunction)
+        self._cached = False
 
         tok_cache_dir: str | None = None  # set inside cache_dir branch when tokenize_fn is CachableTokenizeFunction
         if cache_tag is not None and (cached := self._get_cached_tag(cache_tag, tokenize_fn)) is not None:
+            self._cached = True
             logger.debug(f"[Dataset] Load cached [{self.name}]{self.path} of cache tags {cache_tag}.")
             offset_path = cached["offsets"]
             meta_path = cached.get("jsonl_meta")
@@ -377,6 +379,7 @@ def __init__(
                 _meta_file = os.path.join(tok_cache_dir, "jsonl_meta")
                 if os.path.exists(_meta_file):
                     logger.debug(f"Loading tokenize meta from cache: {_meta_file}")
+                    self._cached = True
                     _meta = load_dict_from_npy_dir(_meta_file, mmap=enable_mmap_shared)
                 else:
                     _meta = self.count_tokens(offsets, tok_cache_dir)
@@ -835,3 +838,7 @@ def load_state_dict(self, state_dict: dict): ...
 
     def get_state_dict(self):
         return {}
+
+    @property
+    def cached(self) -> bool:
+        return self._cached