add missing info

README.md

@@ -7,7 +7,7 @@ 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 s to outperform the existing EfficientNet b0 to b4 and EfficientNetV2 t to l models, whether in TensorFlow or PyTorch, in terms of top-1 accuracy, efficiency, and robustness on my datasets and GVNS benchmarks.
+I built EfficientNetV2.5 s to outperform the existing EfficientNet b0 to b4, EfficientNet b1 to b4 pruned (I pruned b4), and EfficientNetV2 t to l models, whether trained using TensorFlow or PyTorch, in terms of top-1 accuracy, efficiency, and robustness on my datasets and GVNS benchmarks.
 
 ## Model Details
 - **Model tasks:** Image classification / video classification / feature backbone
@@ -15,11 +15,12 @@ I built EfficientNetV2.5 s to outperform the existing EfficientNet b0 to b4 and
   - Params: 16.64 M
   - Multiply-Add Operations: 5.32 G
   - Image size: train = 299x299 / 304x304, test = 304x304
+  - Classification layer: included, and defaults to 1,000 classes
 - **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
+- **Pretrained:** Yes, but requires more pretraining
 - **Original:** This model architecture is original
 
 <br>
@@ -61,4 +62,5 @@ model = torch.load(model_name)
 # Top-1 Accuracy Comparisons
 `efficientnet_b3_pruned` achieved the second highest top-1 accuracy as well as the highest epoch-1 training accuracy on my task, out of all previous EfficientNet models my 24 GB VRAM RTX 3090 could handle.
 
-I will publish the detailed report in another model repository, including the link to the GVNS benchmarks. 
+I will publish the detailed report in another model repository, including the link to the GVNS benchmarks. 
+This repository is only for the base model, pretrained on ImageNet, not my task.