datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
E2AM_ConvNeXtV2_CIFAR10E2AM_ConvNeXtV2Nano
E2AM Ablation Results: ConvNeXtV2-Nano
Energy-aware training ablation study for ConvNeXtV2-Nano across three image-classification datasets: CIFAR-10, CIFAR-100, and Tiny-ImageNet.
Each dataset has 15 training variants (8 individual-method M0..M7, 7 cumulative ablation C0..C6) at 50 epochs, plus a 5-variant deployment pipeline (FP32 baseline, structured pruning, pruning+finetune, INT8 quantization, pruned+INT8).
Status: 45 completed variants, 0 partial. 15 deployment runs.… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/E2AM_ConvNeXtV2Nano.E2AM_ConvNeXtV2Tiny
E2AM Ablation Results: ConvNeXtV2-Tiny
Energy-aware training ablation study for ConvNeXtV2-Tiny across three image-classification datasets: CIFAR-10, CIFAR-100, and Tiny-ImageNet.
Each dataset has 15 training variants (8 individual-method M0..M7, 7 cumulative ablation C0..C6) at 50 epochs, plus a 5-variant deployment pipeline (FP32 baseline, structured pruning, pruning+finetune, INT8 quantization, pruned+INT8).
Status: 45 completed variants, 0 partial. 15 deployment runs.… See the full description on the dataset page: https://huggingface.co/datasets/Shanmuk4622/E2AM_ConvNeXtV2Tiny.E2AM_ConvNeXtV2_TinyImageNetE2AM_ConvNeXtV2_CIFAR100Self-distill-logits-convnext-tiny
ConvNeXt-Tiny experiments — results and prediction archive
Access is configured. The full artifact migration is not complete. This initial publication contains the verified retained-checkpoint/prediction audit and the immutable report-source index, not the bulk checkpoints or full-logit arrays.
Published evidence
Contents
Verified before/after audit
Exact pretrained and epoch-5 random-KL checkpoint identities; 50,000 aligned prediction rows; 78.824% → 79.868%… See the full description on the dataset page: https://huggingface.co/datasets/dlsmarta/Self-distill-logits-convnext-tiny.