Update README.md

README.md

@@ -131,7 +131,7 @@ Dataset is available at [Hugging Face](https://huggingface.co/collections/imageo
 
 The model was trained with the following hyperparameters as specified in the training script:
 - **Base model:** YOLOv11m (yolo11m.pt)
-- **Epochs:** 100
+- **Epochs:** 50
 - **Image size:** 640
 - **Dataset configuration:** Custom YAML file defining 4 classes (Zebra, Giraffe, Onager, Dog)
 - **Training regime:** Default YOLOv11 training parameters
@@ -143,7 +143,7 @@ from ultralytics import YOLO
 model = YOLO("yolo11m.pt")
 results = model.train(
     data="/data/dataset.yaml",
-    epochs=100,
+    epochs=50,
     imgsz=640,
 )
 ```
@@ -168,8 +168,7 @@ The model was evaluated on a held-out test set located at `/fs/ess/PAS2136/Kenya
 #### Factors
 
 The evaluation disaggregated performance by:
-- Species (Zebra, Giraffe, Onager, Dog)
-- [Other evaluation factors if applicable]
+- Species (Zebra, Giraffe, Onager, African wild dog)
 
 #### Metrics
 
@@ -235,12 +234,12 @@ Carbon emissions can be estimated using the [Machine Learning Impact calculator]
 **BibTeX:**
 
 ```
-@software{your_name_yolo11m_2025,
-  author = {Your Name},
+@software{mmla_finetuned_yolo11m,
+  author = {Jenna Kline},
   title = {Fine-Tuned YOLOv11m Animal Detection Model},
   version = {1.0.0},
   year = {2025},
-  url = {https://huggingface.co/your-username/your-model-name}
+  url = {https://huggingface.co/imageomics/mmla}
 }
 ```