Training Setup
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-08.)
Training Setup has 17 facts recorded in Dontopedia across 7 references, with 2 live disagreements.
Mostly:applies to all runs(2), uses(2), has batch size(1)
Maturity scale
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believesNoOverfittingBelieves No Overfitting(1)
- Xenonfun
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containsStructureContains Structure(1)
- Julia 1.txt
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evaluatesAsGoodEvaluates As Good(1)
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isModelArchitectureIs Model Architecture(1)
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Other facts (17)
The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.
| Predicate | Value | Ref |
|---|---|---|
| Applies to All Runs | Adam Run | [1] |
| Applies to All Runs | Rotadamw Run | [1] |
| Uses | Mean Squared Error Loss | [7] |
| Uses | Adam Optimizer | [7] |
| Has Batch Size | 4 | [1] |
| Has Num Iters | 1000 | [1] |
| Has Seq Len | 1024 | [1] |
| Has Val Interval | 1000 | [1] |
| Has Vocab Size | 8000 | [1] |
| Has Warmup Steps | 100 | [1] |
| Not Overfitting Enough | Dropout Need | [2] |
| Uses Data Volume | 136000000 | [2] |
| At Scale | Gpt 2 Scale | [2] |
| Involves Bpe8k Tokenizer | Checkpoints | [3] |
| Exists | True | [4] |
| Not Yet Fancy Method | Fancy Training Method | [5] |
| Assumes Hardware Capable Of12ktoks | True | [6] |
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References (7)
ctx:discord/blah/watt-activation/part-120ctx:discord/blah/watt-activation/part-160ctx:discord/blah/watt-activation/part-262ctx:discord/blah/watt-activation/part-343ctx:discord/blah/watt-activation/part-636ctx:discord/blah/watt-activation/part-168ctx:claims/beam/9dc04f5c-41c0-4f03-9508-0f47a466d19e- full textbeam-chunktext/plain1 KB
doc:beam/9dc04f5c-41c0-4f03-9508-0f47a466d19eShow excerpt
#### Dropout Add dropout layers to your model to randomly drop out a fraction of the neurons during training. ```python import torch import torch.nn as nn import torch.optim as optim from torch.utils.data import DataLoader, TensorDataset …
See also
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