Update README.md

README.md

@@ -129,7 +129,7 @@ Given that GPT-4-turbo was already used in this context for the reference questi
 | **ROUGE-2**|  0.4098          | 0.1751    | 0.3104 |
 | **ROUGE-L**| 0.5809          |  0.2902    | 0.4856  |
 
-_quantum-research-bot-v1.0_ outperformed on all metrics, although _Gemini_ came close in ROUGE-L precision with the difference of only 0.001.
+_quantum-research-bot-v1.0_ outperformed on all metrics, although _Gemini_ came close in BERTScore precision with the difference of only 0.001.
 
 Most other metrics, such as TruthfulQA, MMLU, and similar benchmarks, are not applicable here because this model has been fine-tuned for a very specific domain of knowledge.
 
@@ -176,7 +176,7 @@ For most workloads:
 1 x RTX A6000
 16 vCPU 62 GB RAM
 
-However, when fine tuning `meta-llama/Meta-Llama-3-70B-Instruct` quantization was applied, and I've used 4xA100. Since this did not yield much improvements, and it was very costly, I decided to stick to model with fewer parameters.
+However, when fine tuning `meta-llama/Meta-Llama-3-70B-Instruct`, I've applied quantization with 4xA100 GPUs. Since this did not yield much improvements, and it was very costly, I decided to stick to models with fewer parameters.
 
 
 #### Hardware