Datasets:
Tasks:
Text Classification
Sub-tasks:
sentiment-classification
Languages:
English
Size:
100K<n<1M
License:
Dataset Viewer
The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
Exception: SplitsNotFoundError
Message: The split names could not be parsed from the dataset config.
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 290, in _generate_tables
pa_table = paj.read_json(
io.BytesIO(batch), read_options=paj.ReadOptions(block_size=block_size)
)
File "pyarrow/_json.pyx", line 364, in pyarrow._json.read_json
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
return check_status(status)
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
raise convert_status(status)
pyarrow.lib.ArrowInvalid: JSON parse error: Column() changed from object to string in row 0
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 286, in get_dataset_config_info
for split_generator in builder._split_generators(
~~~~~~~~~~~~~~~~~~~~~~~~~^
StreamingDownloadManager(base_path=builder.base_path, download_config=download_config)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 101, in _split_generators
pa_table = next(iter(self._generate_tables(**splits[0].gen_kwargs, allow_full_read=False)))[1]
~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 304, in _generate_tables
batch = json_encode_fields_in_json_lines(original_batch, json_field_paths)
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 111, in json_encode_fields_in_json_lines
examples = [ujson_loads(line) for line in original_batch.splitlines()]
~~~~~~~~~~~^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/utils/json.py", line 20, in ujson_loads
return pd.io.json.ujson_loads(*args, **kwargs)
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
ValueError: Expected object or value
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/split_names.py", line 68, in compute_split_names_from_streaming_response
for split in get_dataset_split_names(
~~~~~~~~~~~~~~~~~~~~~~~^
path=dataset,
^^^^^^^^^^^^^
config_name=config,
^^^^^^^^^^^^^^^^^^^
token=hf_token,
^^^^^^^^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 340, in get_dataset_split_names
info = get_dataset_config_info(
path,
...<6 lines>...
**config_kwargs,
)
File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 291, in get_dataset_config_info
raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for IMDb Multi-Movie Review Dataset
Dataset Summary
The IMDb Multi-Movie Review Dataset contains approximately 114,000 user reviews collected from over 150 movies on IMDb.
Each movie is stored as a separate JSON file, identified by its movie_id (IMDb ID).
Each JSON file includes a list of structured reviews, where every review consists of:
title: A short summary or headline of the review.review: The full detailed user review.rating: A numeric rating (1–10) as a string.
This dataset supports tasks like sentiment analysis, rating prediction, and text summarization in the domain of movie reviews across multiple genres and time periods.
Supported Tasks and Leaderboards
- Sentiment Classification: Predict sentiment from the review text. Can be used with custom or soft labels.
- Rating Classification/Regression: Predict a 1–10 score from the review text.
- Summarization: Generate a short title-style summary (
title) from the full review (review).
Languages
All reviews are written in English.
Dataset Structure
Each JSON file follows this format:
{
"movie_id": "tt0085750",
"reviews": [
{
"title": "Mediocre, but Oscar worthy compared to part IV.",
"review": "Saw this one in all its 3D glory in the theater back in 1983...",
"rating": "5"
}
]
}
🔧 Load Dataset (from Hugging Face Hub)
from datasets import load_dataset
dataset = load_dataset("Daksh0505/IMDB-Reviews")
print(dataset['train'][0])
Citation (Please add if you use this dataset)
@misc{imdb-multimovie-reviews,
title = {IMDb Multi-Movie Review Dataset},
author = {Daksh Bhardwaj},
year = {2025},
url = {https://huggingface.co/datasets/Daksh0505/IMDB-Reviews
note = {Accessed: 2025-07-17}
}
📂 Dataset URL: https://huggingface.co/datasets/Daksh0505/IMDB-Reviews
🚀 Try the Live Demo
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