19.1 Size and quality — different values

Content and key concepts

Resources, layers and external programme have already been identified.
More parameters require more resources. The usefulness of the result needs to be checked against data; it does not automatically follow from size.
You can divide data, tables, or steps. Partial results need to be linked. Different patterns first turn into vectors of appropriate width, and experts are selected along a limited route.
Для изменения рисунка включитеJavaScript; расчёт и теория доступны далее.
The budget needs to be distributed, not just to increase the model.
Training plan connects the number non-embedding variables
N
the number of tokens
D
, architecture, data quality and compute budget.
C≈6ND
It's useful for the order of magnitude, but it doesn't take into account exact layers, sequence ength, security, recomputation, utilisation, and optimizer overhead.
C
t
r
a
i
n
≈
6
N
D
.
C_{train}\approx 6ND.
C
t
r
ain
​
≈
6
N
D
.
Computer-optimal studies show that, with a fixed budget, parameters and data should be scaled together rather than trained by an increasingly large model on a fixed hull. F15. Scaling law describes an empirical trend in the range studied, but does not show an improvement in eachdownstream, safety or actuality metric.
That's what the model shows.
Budget explorer changes
N
,
D
and available FLOPs and shows only the feasibility message. A single data ledger takes into account unique/effective tokens, epochs, mixture weights and contamination. Repeating the same text increases the processed token, but is not equivalent to the same amount of new information.
Scope of applicability.
FLOP termate is not equal to Wall time, energy, or cost. Extrapolation for the measured range of risk. Parameter account hides artifacture and action alternatives; comparing dense and MoE only by total count is incorrect.
parameters_19a=2_000_000; training_tokens_19a=3_000_000
rough_flops_19a=6*parameters_19a*training_tokens_19a
assert rough_flops_19a==36_000_000_000_000
The code repeats the operations just taken care of.
Completely checked Python-example Chapter
Available with a separate file; the short piece shown does not replace its implementation.
Resources and quality require separate measurements and data.
The same models see different examples. How does this question continue?
Python examples of Chapter 19
Academic base