MU-Bench: Benchmarking Machine Unlearning
Collection
Benchmark machine unlearning (MU) in a wide range of tasks, domains, modalities.
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18 items
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Updated
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This model is a fine-tuned version of facebook/hubert-large-ll60k on the superb dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
Training Loss | Epoch | Step | Validation Loss | Accuracy |
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1.6086 | 1.0 | 1597 | 0.0966 | 0.9826 |
0.2065 | 2.0 | 3194 | 0.0611 | 0.9862 |
0.1822 | 3.0 | 4791 | 0.0541 | 0.9879 |
0.1529 | 4.0 | 6388 | 0.0540 | 0.9869 |
0.1392 | 5.0 | 7985 | 0.0534 | 0.9865 |
0.1307 | 6.0 | 9582 | 0.0464 | 0.9887 |
0.1171 | 7.0 | 11179 | 0.0498 | 0.9873 |
0.1144 | 8.0 | 12776 | 0.0471 | 0.9884 |
0.1104 | 9.0 | 14373 | 0.0455 | 0.9879 |
0.1079 | 10.0 | 15970 | 0.0464 | 0.9885 |
Base model
facebook/hubert-large-ll60k