Model card for efficientnetv2 rw m.agc in1k A EfficientNet v2 image classification model. This is a timm specific variation of the architecture. Trained on ImageNet 1k in timm using recipe template described below. Recipe details: Based on ResNet Strikes Back C recipes SGD (w/ Nesterov) optimizer and AGC (adaptive gradient clipping). Cosine LR schedule with warmup Model Details Model Type: Image classification / feature backbone Model Stats: Params (M): 53.2 GMACs: 12.7 Activations (M): 47.1 Image size: train = 320 x 320, test = 416 x 416 Papers: EfficientNetV2: Smaller Models and Faster Training: https://arxiv.org/abs/2104.00298 ResNet strikes back: An improved training procedure in timm: https://arxiv.org/abs/2110.00476 Dataset: ImageNet 1k Original: https://github.com/huggingface/pytorch image models Model Usage Image Classification Feature Map Extraction Image Embeddings Model Comparison Explore the dataset and runtime metrics of this model in timm model results. Citation
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