Training loop with gradient accumulation
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
Training loop with gradient accumulation has 6 facts recorded in Dontopedia across 2 references, with 1 live disagreement.
Mostly:rdf:type(2), explains(1), refers to(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedOther facts (5)
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 |
|---|---|---|
| Rdf:type | Code Comment | [1] |
| Rdf:type | Comment | [2] |
| Explains | Training Args Instance | [1] |
| Refers to | Gradient Accumulation Steps Setting | [1] |
| Attaches to | Training Loop | [2] |
Timeline
Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.
References (2)
ctx:claims/beam/d63b152b-34b0-4323-aea7-f9df40b773a8- full textbeam-chunktext/plain1 KB
doc:beam/d63b152b-34b0-4323-aea7-f9df40b773a8Show excerpt
#### 1. Data Preprocessing ```python from transformers import LlamaTokenizer import torch # Load tokenizer tokenizer = LlamaTokenizer.from_pretrained("llama-2-13b") # Tokenize dataset def tokenize_function(examples): return tokenizer…
ctx:claims/beam/0a6354af-a6f7-4051-8cb3-e50345232784
See also
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