Row 50852
Content Data
This page contains data entry 50852 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.
> CF happens when a model forgets its previous capabilities when training on a new task.
That is correct.
The main issues I've run into are related to:
* Transfer learning: If tasks share some similarities, a model that forgets can't leverage its prior knowledge for the new task. This makes learning from scratch necessary which can be costly.
* Real-world robustness: Real-world data often has variations within a single task category. A model forgetting everything for slight variations wouldn't be robust.
In essence, catastrophic forgetting can prevent your model from being useful even when the domain is highly specific.
| Field | Value |
|---|---|
| text | > CF happens when a model forgets its previous capabilities when training on a new task. That is correct. The main issues I've run into are related to: * Transfer learning: If tasks share some similarities, a model that forgets can't leverage its prior knowledge for the new task. This makes learning from scratch necessary which can be costly. * Real-world robustness: Real-world data often has variations within a single task category. A model forgetting everything for slight variations wouldn… |
| label | r/deeplearning |
| dataType | comment |
| communityName | r/deeplearning |
| datetime | 2024-05-22 |
| username_encoded | Z0FBQUFBQm5Lak1TNlNGNVVEVjFyMkp2NDhUWkstVzE0TU8xdzdwN1F4T3VVNXFVZkpwQkUxUEVUNVVNS29NVlpjZFg0YmI0LXRIREpmTUs5MndidzFPQV9UaUptbGFQTXQwZFJJa2F0Zk9ZZFVFZmdHTTU2WU09 |
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Raw Record
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"text": "> CF happens when a model forgets its previous capabilities when training on a new task.\n\nThat is correct.\n\nThe main issues I've run into are related to:\n\n* Transfer learning: If tasks share some similarities, a model that forgets can't leverage its prior knowledge for the new task. This makes learning from scratch necessary which can be costly.\n\n* Real-world robustness: Real-world data often has variations within a single task category. A model forgetting everything for slight variations wouldn't be robust.\n\nIn essence, catastrophic forgetting can prevent your model from being useful even when the domain is highly specific.",
"label": "r/deeplearning",
"dataType": "comment",
"communityName": "r/deeplearning",
"datetime": "2024-05-22",
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}
Entry Information
- Entry ID: 50852
- Repository: Axioma AXP
- Dataset: arrmlet/reddit_dataset_36
- Total Entries: 100,000