See pretrain in All languages combined, or Wiktionary
{
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"etymology_text": "Etymology tree\nProto-Indo-European *per-\nProto-Indo-European *preh₂-\nProto-Indo-European *-i\nProto-Indo-European *préh₂i?\nProto-Italic *prai\nProto-Italic *prai-\nLatin prae-lbor.\nMiddle English pre-\nEnglish pre-\nEnglish trainder.\nEnglish pretrain\nFrom pre- + train.",
"forms": [
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{
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{
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{
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{
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"lang_code": "en",
"pos": "verb",
"senses": [
{
"categories": [
{
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"name": "English entries referencing ambiguous etymons",
"parents": [],
"source": "w"
},
{
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"parents": [],
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},
{
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"parents": [],
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{
"kind": "other",
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"parents": [],
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{
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{
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23
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"ref": "2015, Hyeonseob Nam, Bohyung Han, “Learning Multi-Domain Convolutional Neural Networks for Visual Tracking”, in arXiv:",
"text": "Our algorithm pretrains a CNN using a large set of videos with tracking ground-truths to obtain a generic target representation.",
"type": "quotation"
}
],
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"To train (a neural network) on some data set (typically a large generic data set, the output of which one is not directly interested in) before fine-tuning the network on another dataset one is interested in."
],
"id": "en-pretrain-en-verb-fYM7VZMj",
"links": [
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],
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"data set"
],
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"qualifier": "machine learning",
"raw_glosses": [
"(machine learning) To train (a neural network) on some data set (typically a large generic data set, the output of which one is not directly interested in) before fine-tuning the network on another dataset one is interested in."
]
}
],
"word": "pretrain"
}
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"etymology_text": "Etymology tree\nProto-Indo-European *per-\nProto-Indo-European *preh₂-\nProto-Indo-European *-i\nProto-Indo-European *préh₂i?\nProto-Italic *prai\nProto-Italic *prai-\nLatin prae-lbor.\nMiddle English pre-\nEnglish pre-\nEnglish trainder.\nEnglish pretrain\nFrom pre- + train.",
"forms": [
{
"form": "pretrains",
"tags": [
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"singular",
"third-person"
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},
{
"form": "pretraining",
"tags": [
"participle",
"present"
]
},
{
"form": "pretrained",
"tags": [
"participle",
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},
{
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"pos": "verb",
"senses": [
{
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"English entries with etymology trees",
"English entries with etymon",
"English entries with incorrect language header",
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"English terms prefixed with pre-",
"English terms with quotations",
"English verbs",
"Pages using etymon with no ID",
"Pages with 1 entry",
"Pages with entries",
"Pages with etymology trees",
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{
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[
14,
23
]
],
"ref": "2015, Hyeonseob Nam, Bohyung Han, “Learning Multi-Domain Convolutional Neural Networks for Visual Tracking”, in arXiv:",
"text": "Our algorithm pretrains a CNN using a large set of videos with tracking ground-truths to obtain a generic target representation.",
"type": "quotation"
}
],
"glosses": [
"To train (a neural network) on some data set (typically a large generic data set, the output of which one is not directly interested in) before fine-tuning the network on another dataset one is interested in."
],
"links": [
[
"machine learning",
"machine learning"
],
[
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],
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"data set",
"data set"
],
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"fine-tune"
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],
"qualifier": "machine learning",
"raw_glosses": [
"(machine learning) To train (a neural network) on some data set (typically a large generic data set, the output of which one is not directly interested in) before fine-tuning the network on another dataset one is interested in."
]
}
],
"word": "pretrain"
}
Download raw JSONL data for pretrain meaning in English (5.1kB)
This page is a part of the kaikki.org machine-readable English dictionary. This dictionary is based on structured data extracted on 2026-07-25 from the enwiktionary dump dated 2026-07-06 using wiktextract (d9fa233 and 9e92f4b). The data shown on this site has been post-processed and various details (e.g., extra categories) removed, some information disambiguated, and additional data merged from other sources. See the raw data download page for the unprocessed wiktextract data.
If you use this data in academic research, please cite Tatu Ylonen: Wiktextract: Wiktionary as Machine-Readable Structured Data, Proceedings of the 13th Conference on Language Resources and Evaluation (LREC), pp. 1317-1325, Marseille, 20-25 June 2022. Linking to the relevant page(s) under https://kaikki.org would also be greatly appreciated.