{"url":"/dataset/classification-benchmark","name":"classification benchmark","full_name":null,"description_markdown":"This benchmark includes 11 image classification datasets that were used to evaluate the transferability of metrics. Datasets include FGVC Aircraft, Caltech101, Stanford Cars, CIFAR-10, CIFAR-100, DTD, Oxford-102, Flowers, Food-101, Oxford-IIIT Pets, SUN397, and VOC2007 . Please refer to SFDA (https://github.com/TencentARC/SFDA) or ETran (https://github.com/mgholamikn/ETran/tree/main) for further details about the benchmark.","description_withheld":null,"homepage":"","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[],"tasks":[{"name":"Transferability","url":"/task/transferability","datasets_with_task":"/datasets/task/transferability"}],"languages":[],"variants":["classification benchmark"],"data_loaders":[],"num_papers_in_archive":6,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/transferability-on-classification-benchmark","task":"Transferability","dataset_variant":"classification benchmark","rows":6,"metrics":["Kendall's Tau"],"first_row_in_archive_order":{"model":"ETran","paper":"/paper/etran-energy-based-transferability-estimation","metrics":{"Kendall's Tau":"0.562"},"code_links":[{"title":"mgholamikn/ETran","url":"https://github.com/mgholamikn/ETran"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/etran-energy-based-transferability-estimation","title":"ETran: Energy-Based Transferability Estimation","date":"2023-08-03","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":3,"samples_ran":2,"samples_unverified":1,"pointer_only_for_licence":3,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/not-all-models-are-equal-predicting-model","title":"Not All Models Are Equal: Predicting Model Transferability in a Self-challenging Fisher Space","date":"2022-07-07","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":4,"samples_unverified":0,"pointer_only_for_licence":4,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/pactran-pac-bayesian-metrics-for-estimating","title":"PACTran: PAC-Bayesian Metrics for Estimating the Transferability of Pretrained Models to Classification Tasks","date":"2022-03-10","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/logme-practical-assessment-of-pre-trained","title":"LogME: Practical Assessment of Pre-trained Models for Transfer Learning","date":"2021-02-22","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":6,"samples_ran":6,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/ranking-neural-checkpoints-1","title":"Ranking Neural Checkpoints","date":"2020-11-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/leep-a-new-measure-to-evaluate","title":"LEEP: A New Measure to Evaluate Transferability of Learned Representations","date":"2020-02-27","rows_on_this_dataset":1,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":15,"samples_ran":14,"samples_unverified":1,"pointer_only_for_licence":7,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}