[Test] Update the format of the accuracy report (#3081)

### What this PR does / why we need it?
Update the format of the accuracy report

### Does this PR introduce _any_ user-facing change?

### How was this patch tested?

- vLLM version: v0.10.2
- vLLM main:
c60e6137f0

Signed-off-by: hfadzxy <starmoon_zhang@163.com>

tests/e2e/models/configs/DeepSeek-V2-Lite.yaml

@@ -1,4 +1,6 @@
 model_name: "deepseek-ai/DeepSeek-V2-Lite"
+runner: "linux-aarch64-a2-2"
+hardware: "Atlas A2 Series"
 tasks:
 - name: "gsm8k"
   metrics:

tests/e2e/models/configs/Qwen2.5-VL-7B-Instruct.yaml

@@ -1,4 +1,6 @@
 model_name: "Qwen/Qwen2.5-VL-7B-Instruct"
+runner: "linux-aarch64-a2-1"
+hardware: "Atlas A2 Series"
 model: "vllm-vlm"
 tasks:
 - name: "mmmu_val"

tests/e2e/models/configs/Qwen3-30B-A3B.yaml

@@ -1,4 +1,6 @@
 model_name: "Qwen/Qwen3-30B-A3B"
+runner: "linux-aarch64-a2-2"
+hardware: "Atlas A2 Series"
 tasks:
 - name: "gsm8k"
   metrics:

tests/e2e/models/configs/Qwen3-8B-Base.yaml

@@ -1,4 +1,6 @@
 model_name: "Qwen/Qwen3-8B-Base"
+runner: "linux-aarch64-a2-1"
+hardware: "Atlas A2 Series"
 tasks:
 - name: "gsm8k"
   metrics:

tests/e2e/models/configs/accuracy.txt

@@ -1,3 +1,4 @@
+DeepSeek-V2-Lite.yaml
 Qwen3-8B-Base.yaml
 Qwen2.5-VL-7B-Instruct.yaml
 Qwen3-30B-A3B.yaml

tests/e2e/models/report_template.md

@@ -2,16 +2,28 @@
 
 - **vLLM Version**: vLLM: {{ vllm_version }} ([{{ vllm_commit[:7] }}](https://github.com/vllm-project/vllm/commit/{{ vllm_commit }})), **vLLM Ascend Version**: {{ vllm_ascend_version }} ([{{ vllm_ascend_commit[:7] }}](https://github.com/vllm-project/vllm-ascend/commit/{{ vllm_ascend_commit }}))  
 - **Software Environment**: **CANN**: {{ cann_version }}, **PyTorch**: {{ torch_version }}, **torch-npu**: {{ torch_npu_version }}  
-- **Hardware Environment**: Atlas A2 Series  
+- **Hardware Environment**: {{ hardware }}
 - **Parallel mode**: {{ parallel_mode }}
-- **Execution mode**: ACLGraph
+- **Execution mode**: {{ execution_model }}
 
 **Command**:  
 
 ```bash
 export MODEL_ARGS={{ model_args }}
 lm_eval --model {{ model_type }} --model_args $MODEL_ARGS --tasks {{ datasets }} \
-{% if apply_chat_template %} --apply_chat_template {{ apply_chat_template }} {% endif %} {% if fewshot_as_multiturn %} --fewshot_as_multiturn {{ fewshot_as_multiturn }} {% endif %} {% if num_fewshot is defined and num_fewshot != "N/A" %} --num_fewshot {{ num_fewshot }} {% endif %} {% if limit is defined and limit != "N/A" %} --limit {{ limit }} {% endif %} --batch_size {{ batch_size}}
+{% if apply_chat_template is defined and (apply_chat_template|string|lower in ["true", "1"]) -%}
+  --apply_chat_template \
+{%- endif %}
+{% if fewshot_as_multiturn is defined and (fewshot_as_multiturn|string|lower in ["true", "1"]) -%}
+  --fewshot_as_multiturn \
+{%- endif %}
+{% if num_fewshot is defined and num_fewshot != "N/A" -%}
+  --num_fewshot {{ num_fewshot }} \
+{%- endif %}
+{% if limit is defined and limit != "N/A" -%}
+  --limit {{ limit }} \
+{%- endif %}
+--batch_size {{ batch_size }}
 ```
 
 | Task                  | Metric      | Value     | Stderr |

tests/e2e/models/test_lm_eval_correctness.py

@@ -69,6 +69,8 @@ def generate_report(tp_size, eval_config, report_data, report_dir, env_config):
     if model_args.get('enable_expert_parallel', False):
         parallel_mode += " + EP"
 
+    execution_model = f"{'Eager' if model_args.get('enforce_eager', False) else 'ACLGraph'}"
+
     report_content = template.render(
         vllm_version=env_config.vllm_version,
         vllm_commit=env_config.vllm_commit,
@@ -77,6 +79,7 @@ def generate_report(tp_size, eval_config, report_data, report_dir, env_config):
         cann_version=env_config.cann_version,
         torch_version=env_config.torch_version,
         torch_npu_version=env_config.torch_npu_version,
+        hardware=eval_config.get("hardware", "unknown"),
         model_name=eval_config["model_name"],
         model_args=f"'{','.join(f'{k}={v}' for k, v in model_args.items())}'",
         model_type=eval_config.get("model", "vllm"),
@@ -87,7 +90,8 @@ def generate_report(tp_size, eval_config, report_data, report_dir, env_config):
         batch_size=eval_config.get("batch_size", "auto"),
         num_fewshot=eval_config.get("num_fewshot", "N/A"),
         rows=report_data["rows"],
-        parallel_mode=parallel_mode)
+        parallel_mode=parallel_mode,
+        execution_model=execution_model)
 
     report_output = os.path.join(
         report_dir, f"{os.path.basename(eval_config['model_name'])}.md")