Update README.md

README.md

@@ -64,7 +64,7 @@ license: cc-by-nc-4.0
 ![image/png](document_haystacks_fo.gif)
 
 
-This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 250 samples.
+This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 250 samples. It's the 10-page subset of the [full dataset](https://huggingface.co/datasets/AmazonScience/document-haystack).
 
 ## Installation
 
@@ -99,8 +99,8 @@ The benchmark expands on the "Needle in a Haystack" concept by embedding needles
 
 **Key Features:**
 - 25 real-world base documents (annual reports, financial filings, etc.)
-- 5 pages per document variant
-- 5 needles per document (strategically placed across pages)
+- 10 pages per document variant
+- 10 needles per document (strategically placed across pages)
 - Two needle types: text-only and text+image
 - 250 total samples (125 per needle type)
 - 250 retrieval questions
@@ -176,7 +176,7 @@ Questions follow the pattern: **"What is the secret KEY in the document?"**
 This dataset is designed for:
 
 1. **Evaluating VLM retrieval capabilities** - Test how well models can locate specific information within documents
-2. **Benchmarking long-context understanding** - Even at 5 pages, this tests models' ability to process extended visual content
+2. **Benchmarking long-context understanding** - Even at 10 pages, this tests models' ability to process extended visual content
 3. **Comparing text vs. multimodal retrieval** - Direct comparison between text-only and text+image needle performance
 4. **Visual dataset exploration** - Use FiftyOne's visualization tools to understand needle placement patterns
 5. **Model development** - Train and validate models for document understanding tasks