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E2AM-ResNet50
Model Details
- Architecture: ResNet-50
- Initialization: from scratch (
weights=None) - Dataset source: Kaggle ImageFolder or Hugging Face dataset; no torchvision-hosted dataset download is used.
- Energy: NVIDIA-SMI GPU power sampling summed across visible GPUs.
Training Results
| run_id | variant_name | best_f1_score | final_accuracy | final_f1_score | total_energy_j | total_time_sec | total_co2_kg | num_parameters |
|---|---|---|---|---|---|---|---|---|
| cifar10/M2_amp_only | M2_amp_only | 0.666577 | 0.673 | 0.666577 | 477292 | 3803.68 | 0.062976 | 23528522 |
| cifar10/M7_full_e2am | M7_full_e2am | 0.683629 | 0.6851 | 0.683629 | 471771 | 3835.59 | 0.0622476 | 23528522 |
| cifar10/baseline_fixed | baseline_fixed | 0.661276 | 0.6546 | 0.661276 | 1.02776e+06 | 7988.1 | 0.135608 | 23528522 |
Deployment Results
| variant | accuracy | f1_score | latency_ms_per_image | throughput_images_per_sec | energy_per_inference_j | sparsity_percent |
|---|---|---|---|---|---|---|
| fp32 | 0.689063 | 0.687344 | 4.46075 | 224.178 | 0.435256 | 0 |
| pruned | 0.103906 | 0.0257757 | 3.33544 | 299.81 | 0.323063 | 19.9062 |
| pruned_finetuned | 0.665365 | 0.664818 | 3.18521 | 313.951 | 0.301914 | 10.7355 |
| dynamic_linear_int8_cpu | 0.686198 | 0.684309 | 225.033 | 4.4438 | nan | 0 |
Limitations
- Dynamic depth routing is not claimed in this ResNet-50 experiment.
- CPU INT8 energy is not GPU energy and is reported as unavailable.
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