Update README.md

README.md

@@ -16,10 +16,10 @@ BLING models are fine-tuned with high-quality custom instruct datasets, designed
 Evaluated against the benchmark test:   [RAG-Instruct-Benchmark-Tester](https://www.huggingface.co/datasets/llmware/rag_instruct_benchmark_tester)  
 Average of 2 Test Runs with 1 point for correct answer, 0.5 point for partial correct or blank / NF, 0.0 points for incorrect, and -1 points for hallucinations.  
 
---**Accuracy Score**:  **86.0** correct out of 100  
+--**Accuracy Score**:  **86.5** correct out of 100  
 --Not Found Classification:  85.0%  
---Boolean:  85.0%  
---Math/Logic:  37.25%  
+--Boolean:  82.50%  
+--Math/Logic:  37.50%  
 --Complex Questions (1-5):  3 (Medium-High: multiple choice, table reading, causal)  
 --Summarization Quality (1-5):  3 (Coherent, extractive)  
 --Hallucinations:  No hallucinations observed in test runs.  
@@ -34,7 +34,7 @@ For test run results (and good indicator of target use cases), please see the fi
 - **Model type:** TinyLlama
 - **Language(s) (NLP):** English
 - **License:** Apache 2.0
-- **Finetuned from model:** TinyLlama-1.1b
+- **Finetuned from model:** TinyLlama-1.1b - 2.5T checkpoint
 
 ## Uses