Model card for mnasnet 100.rmsp in1k A MNasNet image classification model. Trained on ImageNet 1k in timm using recipe template described below. Recipe details: A simple RmsProp based recipe without RandAugment. Using RandomErasing, mixup, dropout, standard random resize crop augmentation. RMSProp (TF 1.0 behaviour) optimizer, EMA weight averaging Step (exponential decay w/ staircase) LR schedule with warmup Model Details Model Type: Image classification / feature backbone Model Stats: Params (M): 4.4 GMACs: 0.3 Activations (M): 5.5 Image size: 224 x 224 Papers: MnasNet: Platform Aware Neural Architecture Search for Mobi: https://arxiv.org/abs/1807.11626 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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