Update README.md

README.md

@@ -1,13 +1,5 @@
 ---
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: test
-    path: data/test-*
-  - split: valid
-    path: data/valid-*
+license: openrail
 dataset_info:
   features:
   - name: hexsha
@@ -24,17 +16,43 @@ dataset_info:
     dtype: float64
   splits:
   - name: train
-    num_bytes: 3308287053.655602
-    num_examples: 893939
+    num_bytes: 3582248477.9086223
+    num_examples: 806789
   - name: test
-    num_bytes: 183792697.203834
-    num_examples: 49663
+    num_bytes: 394048264.9973618
+    num_examples: 88747
   - name: valid
-    num_bytes: 183796398.001152
-    num_examples: 49664
-  download_size: 1305007590
-  dataset_size: 3675876148.860588
+    num_bytes: 3982797.09401595
+    num_examples: 897
+  download_size: 1323156008
+  dataset_size: 3980279540
+task_categories:
+- text-generation
+language:
+- code
+tags:
+- code
+pretty_name: TheStack-Ruby
+size_categories:
+- 1M<n<10M
 ---
-# Dataset Card for "the-stack-ruby-clean"
 
-[More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
+## Dataset 1: TheStack - Ruby - Cleaned
+
+**Description**: This dataset is drawn from TheStack Corpus, an open-source code dataset with over 3TB of GitHub data covering 48 programming languages. We selected a small portion of this dataset to optimize smaller language models for Ruby, a popular statically typed language.
+
+**Target Language**: Ruby
+
+**Dataset Size**:
+- Training: 900,000 files
+- Validation: 50,000 files
+- Test: 50,000 files
+
+**Preprocessing**:
+1. Selected Ruby as the target language due to its popularity on GitHub.
+2. Filtered out files with average line length > 100 characters, maximum line length > 1000 characters, and alphabet ratio < 25%.
+3. Split files into 90% training, 5% validation, and 5% test sets.
+
+**Tokenizer**: Byte Pair Encoding (BPE) tokenizer with tab and whitespace tokens. GPT-2 vocabulary extended with special tokens.
+
+**Training Sequences**: Sequences constructed by joining training data text to reach a context length of 2048 tokens (1024 tokens for full fine-tuning).