Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2412.10898 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866912156614656000 |
|---|---|
| author | Qiye, Hu Hao, Zhou RuoXi, Yu |
| author_facet | Qiye, Hu Hao, Zhou RuoXi, Yu |
| contents | The phenomenon of grokking in over-parameterized neural networks has garnered significant interest. It involves the neural network initially memorizing the training set with zero training error and near-random test error. Subsequent prolonged training leads to a sharp transition from no generalization to perfect generalization. Our study comprises extensive experiments and an exploration of the research behind the mechanism of grokking. Through experiments, we gained insights into its behavior concerning the training data fraction, the model, and the optimization. The mechanism of grokking has been a subject of various viewpoints proposed by researchers, and we introduce some of these perspectives. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_10898 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Exploring Grokking: Experimental and Mechanistic Investigations Qiye, Hu Hao, Zhou RuoXi, Yu Machine Learning The phenomenon of grokking in over-parameterized neural networks has garnered significant interest. It involves the neural network initially memorizing the training set with zero training error and near-random test error. Subsequent prolonged training leads to a sharp transition from no generalization to perfect generalization. Our study comprises extensive experiments and an exploration of the research behind the mechanism of grokking. Through experiments, we gained insights into its behavior concerning the training data fraction, the model, and the optimization. The mechanism of grokking has been a subject of various viewpoints proposed by researchers, and we introduce some of these perspectives. |
| title | Exploring Grokking: Experimental and Mechanistic Investigations |
| topic | Machine Learning |
| url | https://arxiv.org/abs/2412.10898 |