Update README.md

README.md

@@ -16,7 +16,7 @@ base_model:
 - mistralai/Mistral-Small-24B-Instruct-2501
 pipeline_tag: text-classification
 ---
-# 🔥 Quantized Model: Mistral-Small-24B-Instruct-2501_gptq_g128_4bit 🔥
+# 🔥 Quantized Model: Mistral-Small-24B-Instruct-2501_GPTQ_G128_W4A16_MSE 🔥
 
 This is a 4-bit quantized version of [mistralai/Mistral-Small-24B-Instruct-2501](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501) model, quantized by [ConfidentialMind.com](https://www.confidentialmind.com) 🤖✨  
 It leverages the open-source GPTQModel quantization to achieve 4-bit precision with a group size of 128 resulting in a 
@@ -26,6 +26,7 @@ faster model with minimal performance degradation.
 Ran on a single NVIDIA A100 GPU with 80GB of VRAM.
 
 *Note* `batch_size` is set quite high as the model is small, you may need to adjust this to your GPU VRAM.
+*Note2* Due to the "packed" nature of mistral-small weights, MSE was used agressively along with a higher damping factor - this resulted in lesser loss and perplexity, however G32 is more advised
 
 ## Model Details
 - **Original Model:** [mistralai/Mistral-Small-24B-Instruct-2501](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501)