Update model card

README.md

@@ -11,7 +11,7 @@ tags:
 pipeline_tag: object-detection
 library_name: sgg-benchmark
 model-index:
-  - name: REACT++ yolo12n
+  - name: REACT++ yolo12l
     results:
       - task:
           type: object-detection
@@ -21,36 +21,36 @@ model-index:
           type: psg
         metrics:
           - type: mR@20
-            value: 16.88
+            value: 23.2
             name: mR@20
           - type: R@20
-            value: 26.88
+            value: 30.99
             name: R@20
           - type: F1@20
-            value: 20.74
+            value: 26.53
             name: F1@20
           - type: mR@50
-            value: 18.65
+            value: 25.49
             name: mR@50
           - type: R@50
-            value: 30.61
+            value: 35.3
             name: R@50
           - type: F1@50
-            value: 23.17
+            value: 29.6
             name: F1@50
           - type: mR@100
-            value: 19.5
+            value: 26.45
             name: mR@100
           - type: R@100
-            value: 31.8
+            value: 36.68
             name: R@100
           - type: F1@100
-            value: 24.17
+            value: 30.74
             name: F1@100
           - type: e2e_latency_ms
-            value: 11.4
+            value: 19.6
             name: e2e_latency_ms
-  - name: REACT++ yolo12s
+  - name: REACT++ yolo12m
     results:
       - task:
           type: object-detection
@@ -60,36 +60,36 @@ model-index:
           type: psg
         metrics:
           - type: mR@20
-            value: 21.12
+            value: 22.74
             name: mR@20
           - type: R@20
-            value: 29.28
+            value: 32.69
             name: R@20
           - type: F1@20
-            value: 24.54
+            value: 26.82
             name: F1@20
           - type: mR@50
-            value: 23.21
+            value: 25.21
             name: mR@50
           - type: R@50
-            value: 33.48
+            value: 37.2
             name: R@50
           - type: F1@50
-            value: 27.41
+            value: 30.05
             name: F1@50
           - type: mR@100
-            value: 23.77
+            value: 26.08
             name: mR@100
           - type: R@100
-            value: 34.74
+            value: 38.58
             name: R@100
           - type: F1@100
-            value: 28.23
+            value: 31.12
             name: F1@100
           - type: e2e_latency_ms
-            value: 12.2
+            value: 15.7
             name: e2e_latency_ms
-  - name: REACT++ yolo12m
+  - name: REACT++ yolo12s
     results:
       - task:
           type: object-detection
@@ -99,36 +99,36 @@ model-index:
           type: psg
         metrics:
           - type: mR@20
-            value: 22.74
+            value: 21.12
             name: mR@20
           - type: R@20
-            value: 32.69
+            value: 29.28
             name: R@20
           - type: F1@20
-            value: 26.82
+            value: 24.54
             name: F1@20
           - type: mR@50
-            value: 25.21
+            value: 23.21
             name: mR@50
           - type: R@50
-            value: 37.2
+            value: 33.48
             name: R@50
           - type: F1@50
-            value: 30.05
+            value: 27.41
             name: F1@50
           - type: mR@100
-            value: 26.08
+            value: 23.77
             name: mR@100
           - type: R@100
-            value: 38.58
+            value: 34.74
             name: R@100
           - type: F1@100
-            value: 31.12
+            value: 28.23
             name: F1@100
           - type: e2e_latency_ms
-            value: 15.7
+            value: 12.2
             name: e2e_latency_ms
-  - name: REACT++ yolo12l
+  - name: REACT++ yolo12n
     results:
       - task:
           type: object-detection
@@ -138,34 +138,34 @@ model-index:
           type: psg
         metrics:
           - type: mR@20
-            value: 23.2
+            value: 16.88
             name: mR@20
           - type: R@20
-            value: 30.99
+            value: 26.88
             name: R@20
           - type: F1@20
-            value: 26.53
+            value: 20.74
             name: F1@20
           - type: mR@50
-            value: 25.49
+            value: 18.65
             name: mR@50
           - type: R@50
-            value: 35.3
+            value: 30.61
             name: R@50
           - type: F1@50
-            value: 29.6
+            value: 23.17
             name: F1@50
           - type: mR@100
-            value: 26.45
+            value: 19.5
             name: mR@100
           - type: R@100
-            value: 36.68
+            value: 31.8
             name: R@100
           - type: F1@100
-            value: 30.74
+            value: 24.17
             name: F1@100
           - type: e2e_latency_ms
-            value: 19.6
+            value: 11.4
             name: e2e_latency_ms
   - name: REACT++ yolov8m
     results:
@@ -208,7 +208,7 @@ model-index:
             name: e2e_latency_ms
 ---
 
-# REACT++ Scene Graph Generation — PSG (yolo12n, yolo12s, yolo12m, yolo12l, yolov8m)
+# REACT++ Scene Graph Generation — PSG (yolo12l, yolo12m, yolo12s, yolo12n, yolov8m)
 
 This repository contains **REACT++** model checkpoints for scene graph generation (SGG)
 on the **PSG** benchmark, across 5 backbone sizes.
@@ -235,10 +235,10 @@ The models were trained with the
 
 | Backbone | Params | R@20 | R@50 | R@100 | mR@20 | mR@50 | mR@100 | F1@20 | F1@50 | F1@100 | E2E Lat. (ms) |
 |----------|:------:|-----:|-----:|------:|------:|------:|-------:|------:|------:|-------:|--------------:|
-| yolo12n | ~2.6M | 26.88 | 30.61 | 31.8 | 16.88 | 18.65 | 19.5 | 20.74 | 23.17 | 24.17 | 11.4 |
-| yolo12s | ~9.2M | 29.28 | 33.48 | 34.74 | 21.12 | 23.21 | 23.77 | 24.54 | 27.41 | 28.23 | 12.2 |
-| yolo12m | ~20.2M | 32.69 | 37.2 | 38.58 | 22.74 | 25.21 | 26.08 | 26.82 | 30.05 | 31.12 | 15.7 |
 | yolo12l | ~26.5M | 30.99 | 35.3 | 36.68 | 23.2 | 25.49 | 26.45 | 26.53 | 29.6 | 30.74 | 19.6 |
+| yolo12m | ~20.2M | 32.69 | 37.2 | 38.58 | 22.74 | 25.21 | 26.08 | 26.82 | 30.05 | 31.12 | 15.7 |
+| yolo12s | ~9.2M | 29.28 | 33.48 | 34.74 | 21.12 | 23.21 | 23.77 | 24.54 | 27.41 | 28.23 | 12.2 |
+| yolo12n | ~2.6M | 26.88 | 30.61 | 31.8 | 16.88 | 18.65 | 19.5 | 20.74 | 23.17 | 24.17 | 11.4 |
 | yolov8m | ~25.9M | 30.69 | 35.68 | 37.43 | 22.75 | 25.46 | 26.4 | 26.13 | 29.72 | 30.96 | 15.3 |
 
 ---
@@ -247,10 +247,10 @@ The models were trained with the
 
 | Variant | Sub-folder | Checkpoint files |
 |---------|------------|-----------------|
-| yolo12n | `yolo12n/` | `yolo12n/model.onnx` (ONNX) · `yolo12n/best_model_epoch_5.pth` (PyTorch) |
-| yolo12s | `yolo12s/` | `yolo12s/model.onnx` (ONNX) · `yolo12s/best_model_epoch_6.pth` (PyTorch) |
-| yolo12m | `yolo12m/` | `yolo12m/model.onnx` (ONNX) · `yolo12m/best_model_epoch_9.pth` (PyTorch) |
 | yolo12l | `yolo12l/` | `yolo12l/model.onnx` (ONNX) · `yolo12l/best_model_epoch_9.pth` (PyTorch) |
+| yolo12m | `yolo12m/` | `yolo12m/model.onnx` (ONNX) · `yolo12m/best_model_epoch_9.pth` (PyTorch) |
+| yolo12s | `yolo12s/` | `yolo12s/model.onnx` (ONNX) · `yolo12s/best_model_epoch_6.pth` (PyTorch) |
+| yolo12n | `yolo12n/` | `yolo12n/model.onnx` (ONNX) · `yolo12n/best_model_epoch_5.pth` (PyTorch) |
 | yolov8m | `yolov8m/` | `yolov8m/model.onnx` (ONNX) · `yolov8m/best_model_epoch_6.pth` (PyTorch) |
 
 ---
@@ -264,7 +264,7 @@ from huggingface_hub import hf_hub_download
 
 onnx_path = hf_hub_download(
     repo_id="maelic/REACTPlusPlus_PSG",
-    filename="yolo12n/model.onnx",
+    filename="yolo12l/model.onnx",
     repo_type="model",
 )
 # Run with tools/eval_onnx_psg.py or load directly via onnxruntime
@@ -284,12 +284,12 @@ from huggingface_hub import hf_hub_download
 
 ckpt_path = hf_hub_download(
     repo_id="maelic/REACTPlusPlus_PSG",
-    filename="yolo12n/best_model.pth",
+    filename="yolo12l/best_model.pth",
     repo_type="model",
 )
 cfg_path = hf_hub_download(
     repo_id="maelic/REACTPlusPlus_PSG",
-    filename="yolo12n/hydra_config.yaml",
+    filename="yolo12l/config.yml",
     repo_type="model",
 )