Create README.md

README.md

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+# Common Crawl sample
+
+A small unofficial random subset of the famous Common Crawl dataset.
+
+- 60 random segment WET files were downloaded from [Common Crawl](https://commoncrawl.org/) on 2024-05-12.
+- Lines between 500 and 5000 characters long (inclusive) were kept.
+- Only unique texts were kept.
+- No other filtering.
+
+## Languages
+
+- Each text was assigned to one of the [language codes](https://github.com/google/cld3?tab=readme-ov-file#supported-languages) using the GCLD3 Python package.
+- The Chinese texts were classified as either simplified, traditional, or Cantonese using the [fastlangid package](https://github.com/currentslab/fastlangid).
+- For each language, 10% of the rows were randomly selected as the test set.
+- The test set of the "all" languages split is the union of the test sets of all the languages in the dataset.
+
+:warning: **Warning!** :no_entry_sign:
+- This dataset is raw and unfiltered from the Internet.
+- So it contains objectionable content, false information, and possibly personally identifiable information. 
+- But it's mostly spam and repetitive junk. Just spam, spam, spam. Spam everywhere. :poop: Please filter it according to your needs.
+
+## Limitations
+
+- Some languages are greatly overrepresented.
+- Samples of webpages may not represent real language use.
+- Major problem is spam. Throws off the language detectors.
+- Many false positives like Taiwanese traditional Chinese being classified as Cantonese.
+- The testing split isn't truly independent of the training split
+	- for example, different paragraphs from the same webpage can end up in both training and testing splits