Update README.md

README.md

@@ -125,10 +125,11 @@ model.save_pretrained("Meta-Llama-3.1-8B-Instruct-quantized.w8a16")
 
 The model was evaluated on MMLU, ARC-Challenge, GSM-8K, Hellaswag, Winogrande and TruthfulQA.
 Evaluation was conducted using the Neural Magic fork of [lm-evaluation-harness](https://github.com/neuralmagic/lm-evaluation-harness/tree/llama_3.1_instruct) (branch llama_3.1_instruct) and the [vLLM](https://docs.vllm.ai/en/stable/) engine.
-This version of the lm-evaluation-harness includes versions of ARC-Challenge and GSM-8K that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-8B-Instruct-evals).
+This version of the lm-evaluation-harness includes versions of MMLU, ARC-Challenge and GSM-8K that match the prompting style of [Meta-Llama-3.1-Instruct-evals](https://huggingface.co/datasets/meta-llama/Meta-Llama-3.1-8B-Instruct-evals).
 
 ### Accuracy
 
+#### Open LLM Leaderboard evaluation scores
 <table>
   <tr>
    <td><strong>Benchmark</strong>
@@ -143,29 +144,39 @@ This version of the lm-evaluation-harness includes versions of ARC-Challenge and
   <tr>
    <td>MMLU (5-shot)
    </td>
-   <td>67.94
+   <td>69.43
    </td>
-   <td>68.09
+   <td>69.37
    </td>
-   <td>100.2%
+   <td>99.9%
    </td>
   </tr>
   <tr>
-   <td>ARC Challenge (0-shot)
+   <td>MMLU (CoT, 0-shot)
    </td>
-   <td>83.19
+   <td>72.56
    </td>
-   <td>82.68
+   <td>72.14
    </td>
    <td>99.4%
    </td>
   </tr>
+  <tr>
+   <td>ARC Challenge (0-shot)
+   </td>
+   <td>81.57
+   </td>
+   <td>81.48
+   </td>
+   <td>99.9%
+   </td>
+  </tr>
   <tr>
    <td>GSM-8K (CoT, 8-shot, strict-match)
    </td>
    <td>82.79
    </td>
-   <td>82.64
+   <td>81.64
    </td>
    <td>99.8%
    </td>
@@ -175,7 +186,7 @@ This version of the lm-evaluation-harness includes versions of ARC-Challenge and
    </td>
    <td>80.01
    </td>
-   <td>80.21
+   <td>80.1
    </td>
    <td>100.3%
    </td>
@@ -203,9 +214,9 @@ This version of the lm-evaluation-harness includes versions of ARC-Challenge and
   <tr>
    <td><strong>Average</strong>
    </td>
-   <td><strong>74.31</strong>
+   <td><strong>74.04</strong>
    </td>
-   <td><strong>74.17</strong>
+   <td><strong>73.89</strong>
    </td>
    <td><strong>99.8%</strong>
    </td>
@@ -220,17 +231,30 @@ The results were obtained using the following commands:
 ```
 lm_eval \
   --model vllm \
-  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1 \
-  --tasks mmlu \
+  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
+  --tasks mmlu_llama_3.1_instruct \
+  --fewshot_as_multiturn \
+  --apply_chat_template \
   --num_fewshot 5 \
   --batch_size auto
 ```
 
+#### MMLU-CoT
+```
+lm_eval \
+  --model vllm \
+  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=4064,max_gen_toks=1024,tensor_parallel_size=1 \
+  --tasks mmlu_cot_0shot_llama_3.1_instruct \
+  --apply_chat_template \
+  --num_fewshot 0 \
+  --batch_size auto
+```
+
 #### ARC-Challenge
 ```
 lm_eval \
   --model vllm \
-  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1 \
+  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=3940,max_gen_toks=100,tensor_parallel_size=1 \
   --tasks arc_challenge_llama_3.1_instruct \
   --apply_chat_template \
   --num_fewshot 0 \
@@ -241,7 +265,7 @@ lm_eval \
 ```
 lm_eval \
   --model vllm \
-  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1 \
+  --model_args pretrained="neuralmagic/Meta-Llama-3.1-8B-Instruct-quantized.w8a16",dtype=auto,add_bos_token=True,max_model_len=4096,max_gen_toks=1024,tensor_parallel_size=1 \
   --tasks gsm8k_cot_llama_3.1_instruct \
   --fewshot_as_multiturn \
   --apply_chat_template \