Update README: rename repository references to UltraData-Math

README.md

@@ -18,8 +18,6 @@ tags:
 - high-quality
 - mathematical-reasoning
 configs:
-- config_name: UltraData-Math-L1
-  data_files: "data/UltraData-Math-L1/**/*.parquet"
 - config_name: UltraData-Math-L3-Conversation-Synthetic
   data_files: "data/UltraData-Math-L3/Conversation-Synthetic/*.parquet"
 - config_name: UltraData-Math-L3-Multi-Style-Synthetic
@@ -28,6 +26,8 @@ configs:
   data_files: "data/UltraData-Math-L3/QA-Synthetic/*.parquet"
 - config_name: UltraData-Math-L3-Textbook-Exercise-Synthetic
   data_files: "data/UltraData-Math-L3/Textbook-Exercise-Synthetic/*.parquet"
+- config_name: UltraData-Math-L1
+  data_files: "data/UltraData-Math-L1/**/*.parquet"
 default_config_name: UltraData-Math-L3-Conversation-Synthetic
 ---
 
@@ -39,7 +39,7 @@ default_config_name: UltraData-Math-L3-Conversation-Synthetic
 
 <div align="center">
 
-[🤗 Dataset](https://huggingface.co/datasets/openbmb/UltraData-Math-L1) | [💻 Code Repository](https://github.com/UltraData-OpenBMB/UltraData-Math) | [🇨🇳 中文 README](README_ZH.md)
+[🤗 Dataset](https://huggingface.co/datasets/openbmb/UltraData-Math) | [💻 Code Repository](https://github.com/UltraData-OpenBMB/UltraData-Math) | [🇨🇳 中文 README](README_ZH.md)
 
 
 </div>
@@ -63,7 +63,7 @@ Experiments show that on the MiniCPM-1B architecture, ***UltraData-Math*** achie
 
 ***UltraData-Math*** has been applied to the mathematical pre-training of the [MiniCPM Series](https://huggingface.co/collections/openbmb/minicpm-4-6841ab29d180257e940baa9b) models.
 
-- **[UltraData-Math-L1](https://huggingface.co/datasets/openbmb/UltraData-Math-L1)**: Large-scale high-quality mathematical pre-training dataset, containing 159.4B tokens of web mathematical corpus. (**<-- you are here**)
+- **[UltraData-Math-L1](https://huggingface.co/datasets/openbmb/UltraData-Math)**: Large-scale high-quality mathematical pre-training dataset, containing 159.4B tokens of web mathematical corpus. (**<-- you are here**)
 - **[UltraData-Math-L3](https://huggingface.co/datasets/openbmb/UltraData-Math-L3)**: High-quality synthetic mathematical dataset, containing 37.1B tokens of multi-format synthetic data (Q&A, multi-turn dialogues, knowledge textbooks, etc.).
 
 ## 🏗️ Data Processing Pipeline
@@ -123,8 +123,8 @@ Natural web data is mostly declarative text. To enhance the model's instruction
 
 | Dataset | # Tokens | # Documents |
 |:---|:---:|:---:|
-| UltraData-Math-L1 | 159.4B | 85.56M |
-| UltraData-Math-L3 | 37.1B | 31.87M |
+| UltraData-Math-L1 | 170.5B | 85.6M |
+| UltraData-Math-L3 | 88B | 81.4M |
 
 ## 📈 Experimental Results
 
@@ -134,9 +134,9 @@ We used the **MiniCPM-1.2B** model architecture and **MiniCPM3-4B** tokenizer fo
 - **Code Generation:** HumanEval, MBPP
 - **Comprehensive Knowledge:** MMLU, MMLU-STEM
 
-### L0 Parser Ablation Study
+### L0 Parser Comparison
 
-Based on data from the same source, we used different parsers for extraction and trained independently to directly compare the effects of parsing strategies:
+Based on data from the same source, we re-parsed the raw HTML using different parsers and applied the same L1 cleaning operators to all parsed results. Each cleaned dataset was then used for independent training to directly compare the effects of parsing strategies:
 
 | Parser | Average | MMLU | GSM8K | HumanEval | math | mbpp_full | mmlu-stem |
 |:---|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
@@ -146,6 +146,8 @@ Based on data from the same source, we used different parsers for extraction and
 | Megamath | 42.32 | **51.46** | 54.06 | 29.88 | 26.04 | 45.64 | **46.81** |
 | magic-html + w3m | 41.29 | 51.23 | 51.63 | 26.83 | 26.58 | 45.02 | 46.45 |
 
+
+
 ### Full Evaluation Results
 
 We used a single dataset for independent training to directly compare the effects of different data sources: