add model details

README.md

@@ -8,6 +8,18 @@ license: cc-by-nc-4.0
 
 To be clear, this model is tailored to my image and video classification tasks, not to imagenet. I built EfficientNetV2.5 to outperform the existing EfficientNet b0 to b7 and EfficientNetV2 t to xl models, whether in TensorFlow or PyTorch, in terms of top-1 accuracy, efficiency, and robustness on my datasets and benchmarks.
 
+## Model Details
+- **Model tasks:** Image classification / video classification / feature backbone
+- **Model stats:**
+  - Params: 16.64 M
+  - Multiply-Add Operations: 5.32 G
+  - Image size: train = 299x299 / 304x304, test = 304x304
+- **Papers:**
+  - EfficientNetV2: Smaller Models and Faster Training: https://arxiv.org/abs/2104.00298
+  - Layer-adaptive sparsity for the Magnitude-based Pruning: https://arxiv.org/abs/2010.07611
+- **Dataset:** ImageNet-1k
+- **Pretrained:** Yes, but requires finetuning
+- **Original:** This model architecture is original
 
 To change the number of classes, replace the linear classification layer. 
 Here's an example to convert the architecture into a training-ready model.