Create README.md

README.md

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+---
+dataset_name: grammar-correction
+description: >
+  A refined subset of the liweili/c4_200m dataset, derived from Google's C4_200M Synthetic Dataset for Grammatical Error Correction. 
+  Contains sentence pairs where the input is ungrammatical and the output is grammatical, suitable for training grammatical error correction (GEC) models.
+train_size: 100000
+validation_size: 25000
+data_fields:
+  - input: "Ungrammatical sentence (string)"
+  - output: "Corrected, grammatical sentence (string)"
+intended_uses: >
+  Designed for training and evaluating GEC models to automatically identify and correct grammatical errors in text.
+limitations:
+  - "Synthetic data may not fully capture real-world grammatical errors."
+  - "Filtering may introduce biases based on classifier performance."
+  - "Focused on English grammar, limiting applicability to other languages or dialects."
+---
+# grammar-correction
+
+## Dataset Summary
+
+The grammar-correction dataset is a refined subset of the [liweili/c4_200m](https://huggingface.co/datasets/liweili/c4_200m) dataset, 
+derived from Google's [C4_200M Synthetic Dataset for Grammatical Error Correction](https://github.com/google-research-datasets/C4_200M-synthetic-dataset-for-grammatical-error-correction). 
+It contains sentence pairs where the input is ungrammatical and the output is grammatical, making it suitable for training grammatical error correction (GEC) models.
+
+## Dataset Structure
+
+- **Train set**: 100 000 entries
+- **Validation set**: 25 000 entries
+
+### Data Fields
+
+- **input**: Ungrammatical sentence (string)
+- **output**: Corrected, grammatical sentence (string)
+
+## Dataset Creation
+
+### Source Data
+
+This dataset is based on the liweili/c4_200m dataset, which includes 185 million sentence pairs generated from a cleaned English corpus.
+
+### Filtering Methodology
+
+Entries were filtered using the [agentlans/snowflake-arctic-xs-grammar-classifier](https://huggingface.co/agentlans/snowflake-arctic-xs-grammar-classifier) 
+to retain only those with ungrammatical inputs and grammatical outputs, enhancing the quality of training data for GEC tasks.
+
+## Considerations for Using the Data
+
+### Intended Uses
+
+Designed for training and evaluating GEC models to automatically identify and correct grammatical errors in text.
+
+### Limitations and Biases
+
+1. The dataset is synthetic and may not fully capture real-world grammatical errors.
+2. Filtering may introduce biases based on classifier performance.
+3. Focused on English grammar, limiting applicability to other languages or dialects.
+
+## Additional Information
+
+### Dataset Curators
+
+- Curated by filtering the liweili/c4_200m dataset, based on Google's C4_200M dataset.
+- Please check the licenses of those datasets for usage rights.
+- Also acknowledge the use of the agentlans/snowflake-arctic-xs-grammar-classifier for filtering.
+
+### Contributions
+
+This dataset aims to provide high-quality resources for GEC model training and evaluation, building on the efforts of Google Research and the Hugging Face community.