kaustubhgap
commited on
Commit
•
993d0ac
1
Parent(s):
29b03ca
Push model using huggingface_hub.
Browse files- 1_Pooling/config.json +10 -0
- README.md +475 -0
- config.json +24 -0
- config_sentence_transformers.json +10 -0
- config_setfit.json +4 -0
- model.safetensors +3 -0
- model_head.pkl +3 -0
- modules.json +14 -0
- sentence_bert_config.json +4 -0
- special_tokens_map.json +51 -0
- tokenizer.json +0 -0
- tokenizer_config.json +59 -0
- vocab.txt +0 -0
1_Pooling/config.json
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{
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"word_embedding_dimension": 768,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": true,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": false,
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"include_prompt": true
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}
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README.md
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---
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base_model: sentence-transformers/paraphrase-mpnet-base-v2
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library_name: setfit
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metrics:
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- accuracy
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pipeline_tag: text-classification
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tags:
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- setfit
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- sentence-transformers
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- text-classification
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- generated_from_setfit_trainer
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widget:
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- text: one piece
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- text: tube
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- text: heavy weight
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- text: track
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- text: unitard
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inference: true
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model-index:
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- name: SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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results:
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- task:
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type: text-classification
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name: Text Classification
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dataset:
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name: Unknown
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type: unknown
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split: test
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metrics:
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- type: accuracy
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value: 0.5493273542600897
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name: Accuracy
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---
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# SetFit with sentence-transformers/paraphrase-mpnet-base-v2
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This is a [SetFit](https://github.com/huggingface/setfit) model that can be used for Text Classification. This SetFit model uses [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2) as the Sentence Transformer embedding model. A [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance is used for classification.
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The model has been trained using an efficient few-shot learning technique that involves:
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1. Fine-tuning a [Sentence Transformer](https://www.sbert.net) with contrastive learning.
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2. Training a classification head with features from the fine-tuned Sentence Transformer.
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## Model Details
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### Model Description
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- **Model Type:** SetFit
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- **Sentence Transformer body:** [sentence-transformers/paraphrase-mpnet-base-v2](https://huggingface.co/sentence-transformers/paraphrase-mpnet-base-v2)
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- **Classification head:** a [LogisticRegression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html) instance
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- **Maximum Sequence Length:** 512 tokens
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- **Number of Classes:** 119 classes
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<!-- - **Training Dataset:** [Unknown](https://huggingface.co/datasets/unknown) -->
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<!-- - **Language:** Unknown -->
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<!-- - **License:** Unknown -->
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### Model Sources
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- **Repository:** [SetFit on GitHub](https://github.com/huggingface/setfit)
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- **Paper:** [Efficient Few-Shot Learning Without Prompts](https://arxiv.org/abs/2209.11055)
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- **Blogpost:** [SetFit: Efficient Few-Shot Learning Without Prompts](https://huggingface.co/blog/setfit)
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### Model Labels
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| Label | Examples |
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|:------|:---------------------------------------------------------------------------------------------------|
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| 79 | <ul><li>'peony middle notes'</li><li>'lemon middle notes'</li><li>'coconut middle notes'</li></ul> |
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| 86 | <ul><li>'no print/no pattern'</li><li>'two tone'</li><li>'diagonal stripe'</li></ul> |
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| 37 | <ul><li>'eel skin leather'</li><li>'metal'</li><li>'raffia'</li></ul> |
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| 82 | <ul><li>'collarless'</li><li>'peaked lapel'</li><li>'front keyhole'</li></ul> |
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| 95 | <ul><li>'standard toe'</li><li>'wide toe'</li><li>'extra wide toe'</li></ul> |
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| 83 | <ul><li>'indoor'</li><li>'hike'</li><li>'beach'</li></ul> |
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| 107 | <ul><li>'surplice'</li><li>'messenger bag'</li><li>'camera bag'</li></ul> |
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| 19 | <ul><li>'mary jane'</li><li>'zip around wallet'</li><li>'tongue buckle'</li></ul> |
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| 102 | <ul><li>'slits at knee'</li><li>'slits above hips'</li><li>'front slit at hem'</li></ul> |
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| 35 | <ul><li>'tie'</li><li>'gem embellishment'</li><li>'caged'</li></ul> |
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| 18 | <ul><li>'rolo chain'</li><li>'cord bracelet'</li><li>'figaro'</li></ul> |
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| 65 | <ul><li>'wheat protein'</li><li>'rosemary ingredient'</li><li>'pea protein'</li></ul> |
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| 68 | <ul><li>'bath towel'</li><li>'art print'</li><li>'reusable bottle'</li></ul> |
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| 40 | <ul><li>'polyfill'</li><li>'silk fill'</li><li>'feather fill'</li></ul> |
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| 50 | <ul><li>'palm grip'</li><li>'carpenter hook'</li><li>'storm flap'</li></ul> |
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| 113 | <ul><li>'wide waistband'</li><li>'elastic inset'</li><li>'belt loops'</li></ul> |
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| 75 | <ul><li>'glass'</li><li>'acrylic'</li><li>'opal'</li></ul> |
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| 11 | <ul><li>'foam cups'</li><li>'wire'</li><li>'molded cups'</li></ul> |
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| 38 | <ul><li>'dual layer fabric'</li><li>'2 way stretch'</li><li>'4 way stretch'</li></ul> |
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| 63 | <ul><li>'light support'</li><li>'medium supprt'</li><li>'high support'</li></ul> |
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| 44 | <ul><li>'face'</li><li>'hand'</li><li>'neck/dècolletage'</li></ul> |
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| 115 | <ul><li>'soy wax'</li><li>'paraffin wax'</li></ul> |
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| 42 | <ul><li>'regular'</li><li>'tailored'</li><li>'fitted'</li></ul> |
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| 97 | <ul><li>'king'</li><li>'euro'</li><li>'standard'</li></ul> |
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| 70 | <ul><li>'wrist length'</li><li>'above thigh'</li><li>'below bust'</li></ul> |
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| 34 | <ul><li>'feminine'</li><li>'religious'</li><li>'boho'</li></ul> |
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| 10 | <ul><li>'slim'</li><li>'regular'</li></ul> |
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| 15 | <ul><li>'6-10 oz'</li><li>'11-20 oz'</li></ul> |
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| 77 | <ul><li>'rose gold metal'</li><li>'gold plated'</li><li>'alloy'</li></ul> |
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| 43 | <ul><li>'contrast inner lining'</li><li>'simple seaming'</li><li>'princess seams'</li></ul> |
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| 7 | <ul><li>'neroli base notes'</li><li>'amber base notes'</li><li>'musk base notes'</li></ul> |
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| 17 | <ul><li>'spot clean'</li><li>'dry clean'</li><li>'microwave safe'</li></ul> |
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| 8 | <ul><li>'nourishing'</li><li>'firming'</li><li>'soothing/healing'</li></ul> |
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| 103 | <ul><li>'lugged soles'</li><li>'non marking soles'</li></ul> |
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| 26 | <ul><li>'wall control'</li><li>'switch control'</li></ul> |
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| 99 | <ul><li>'fitted sleeves'</li><li>'fitted sleeve'</li><li>'structured sleeves'</li></ul> |
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| 33 | <ul><li>'rim'</li><li>'feet'</li><li>'5 panel construction'</li></ul> |
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| 64 | <ul><li>'mineral oil free'</li><li>'propylene glycol free'</li><li>'paraffin free'</li></ul> |
|
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| 96 | <ul><li>'double strap'</li><li>'spaghetti straps'</li><li>'thin straps'</li></ul> |
|
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| 1 | <ul><li>'shoulder back'</li><li>'full coverage'</li><li>'low back'</li></ul> |
|
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| 62 | <ul><li>'rustic'</li><li>'coastal'</li><li>'scandinavian'</li></ul> |
|
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| 39 | <ul><li>'metallic'</li><li>'swiss dot'</li><li>'base layer'</li></ul> |
|
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| 60 | <ul><li>'halloween'</li><li>'christmas holiday'</li></ul> |
|
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| 92 | <ul><li>'seamless'</li><li>'mid rise waist seam'</li><li>'flat seam'</li></ul> |
|
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| 114 | <ul><li>'ultra high rise'</li><li>'mid rise'</li><li>'high waisted'</li></ul> |
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| 105 | <ul><li>'top handle'</li><li>'detachable straps'</li><li>'chain strap'</li></ul> |
|
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+
| 90 | <ul><li>'floral'</li><li>'psychedelic print'</li><li>'paisley'</li></ul> |
|
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| 91 | <ul><li>'night'</li><li>'day'</li></ul> |
|
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| 45 | <ul><li>'serum formulation'</li><li>'cream/creme'</li><li>'solid'</li></ul> |
|
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+
| 59 | <ul><li>'strong hold'</li><li>'flexible hold'</li></ul> |
|
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+
| 46 | <ul><li>'leather'</li><li>'fresh aquatic'</li><li>'green aromatic'</li></ul> |
|
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| 21 | <ul><li>'matte'</li><li>'metallic'</li><li>'olive'</li></ul> |
|
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+
| 69 | <ul><li>'cinnamon key notes'</li><li>'violet key notes'</li><li>'pepper key notes'</li></ul> |
|
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| 101 | <ul><li>'dropped shoulder'</li><li>'puff shoulder'</li><li>'flutter sleeve'</li></ul> |
|
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| 61 | <ul><li>'summer'</li><li>'everyday'</li><li>'indoor'</li></ul> |
|
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| 104 | <ul><li>'wedding guest'</li><li>'bridal'</li><li>'halloween'</li></ul> |
|
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| 32 | <ul><li>'indigo wash'</li><li>'acid wash'</li><li>'stonewash'</li></ul> |
|
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| 51 | <ul><li>'still life graphic'</li><li>'sports graphic'</li><li>'star wars'</li></ul> |
|
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| 48 | <ul><li>'beige'</li><li>'black'</li><li>'rose gold frame'</li></ul> |
|
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| 87 | <ul><li>'medium pile'</li><li>'low pile'</li></ul> |
|
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| 22 | <ul><li>'bright'</li><li>'pastel'</li><li>'light'</li></ul> |
|
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| 41 | <ul><li>'matte finish'</li><li>'shiny finish'</li></ul> |
|
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| 93 | <ul><li>'no buckle'</li><li>'geometric shape'</li><li>'straight silhouette'</li></ul> |
|
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+
| 71 | <ul><li>'polarized'</li><li>'color tinted'</li><li>'mirrored'</li></ul> |
|
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| 2 | <ul><li>'split back'</li><li>'racer back'</li><li>'open back'</li></ul> |
|
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| 89 | <ul><li>'round stitch pocket'</li><li>'seam pocket'</li><li>'kangaroo pocket'</li></ul> |
|
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| 20 | <ul><li>'removable hoodie'</li><li>'packable hood collar'</li><li>'hooded'</li></ul> |
|
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| 52 | <ul><li>'thick'</li><li>'medium thick'</li></ul> |
|
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| 55 | <ul><li>'amber head notes'</li><li>'lime head notes'</li><li>'musk head notes'</li></ul> |
|
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| 58 | <ul><li>'back curved hem'</li><li>'twist hem'</li><li>'ribbed hem'</li></ul> |
|
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| 118 | <ul><li>'light wood'</li><li>'medium wood'</li></ul> |
|
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| 25 | <ul><li>'gifts for him'</li><li>'apres ski'</li><li>'cozy'</li></ul> |
|
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| 109 | <ul><li>'closed toe'</li><li>'square toe'</li><li>'round toe'</li></ul> |
|
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| 30 | <ul><li>'extended cuffs'</li><li>'storm cuffs'</li><li>'elastic cuff'</li></ul> |
|
139 |
+
| 24 | <ul><li>'ingrown hairs'</li><li>'frizz'</li><li>'redness'</li></ul> |
|
140 |
+
| 9 | <ul><li>'high cut'</li><li>'string bikini'</li></ul> |
|
141 |
+
| 94 | <ul><li>'opaque'</li><li>'sheer'</li></ul> |
|
142 |
+
| 16 | <ul><li>'2 card slot'</li><li>'card slots'</li></ul> |
|
143 |
+
| 78 | <ul><li>'gothcore'</li><li>'vanilla girl'</li><li>'dyed out'</li></ul> |
|
144 |
+
| 4 | <ul><li>'layered'</li><li>'bangle'</li><li>'cuff'</li></ul> |
|
145 |
+
| 23 | <ul><li>'parfum'</li><li>'eau de toilette'</li></ul> |
|
146 |
+
| 111 | <ul><li>'delicate'</li><li>'statement'</li></ul> |
|
147 |
+
| 12 | <ul><li>'flat brim'</li><li>'curved brim'</li><li>'fold over brim'</li></ul> |
|
148 |
+
| 98 | <ul><li>'dry'</li><li>'acne prone'</li><li>'mature'</li></ul> |
|
149 |
+
| 57 | <ul><li>'stacked heel'</li><li>'kitten heel'</li><li>'cone heel'</li></ul> |
|
150 |
+
| 67 | <ul><li>'id slot'</li><li>'interior pocket'</li><li>'interior zipper pocket'</li></ul> |
|
151 |
+
| 31 | <ul><li>'light wash'</li><li>'medium wash'</li><li>'colored'</li></ul> |
|
152 |
+
| 85 | <ul><li>'detailed stitching pant'</li><li>'simple seaming'</li></ul> |
|
153 |
+
| 116 | <ul><li>'knotted'</li><li>'percale'</li><li>'waffle weave'</li></ul> |
|
154 |
+
| 88 | <ul><li>'shag'</li><li>'cut pile'</li></ul> |
|
155 |
+
| 74 | <ul><li>'study hall'</li><li>'y2k'</li><li>'enchanted'</li></ul> |
|
156 |
+
| 72 | <ul><li>'fur'</li><li>'fleece'</li><li>'mesh'</li></ul> |
|
157 |
+
| 108 | <ul><li>'animal'</li><li>'love'</li></ul> |
|
158 |
+
| 73 | <ul><li>'unlined'</li><li>'fully lined'</li><li>'partially lined'</li></ul> |
|
159 |
+
| 13 | <ul><li>'wide brim'</li><li>'medium brim'</li></ul> |
|
160 |
+
| 76 | <ul><li>'bpa free material'</li><li>'scratch resistant material'</li></ul> |
|
161 |
+
| 54 | <ul><li>'straight handle'</li><li>'curved handle'</li></ul> |
|
162 |
+
| 100 | <ul><li>'rolled up sleeves'</li><li>'3/4 sleeve'</li><li>'bracelet length'</li></ul> |
|
163 |
+
| 84 | <ul><li>'manual open'</li><li>'auto open'</li></ul> |
|
164 |
+
| 14 | <ul><li>'wide'</li><li>'medium'</li></ul> |
|
165 |
+
| 27 | <ul><li>'superhero'</li><li>'disney'</li></ul> |
|
166 |
+
| 49 | <ul><li>'half rim'</li><li>'full rim'</li></ul> |
|
167 |
+
| 29 | <ul><li>'tall crown'</li><li>'short crown'</li></ul> |
|
168 |
+
| 106 | <ul><li>'low stretch'</li><li>'non stretch'</li></ul> |
|
169 |
+
| 112 | <ul><li>'mid vamp'</li><li>'high vamp'</li></ul> |
|
170 |
+
| 66 | <ul><li>'large interior'</li><li>'medium interior'</li><li>'small interior'</li></ul> |
|
171 |
+
| 53 | <ul><li>'all hair types'</li><li>'damaged/dry hair'</li></ul> |
|
172 |
+
| 117 | <ul><li>'light weight'</li><li>'mid weight'</li></ul> |
|
173 |
+
| 81 | <ul><li>'low cut'</li><li>'mid chest neckline'</li><li>'open front'</li></ul> |
|
174 |
+
| 5 | <ul><li>'thin band'</li><li>'soft band elastic'</li><li>'elastic band'</li></ul> |
|
175 |
+
| 28 | <ul><li>'flat top crown'</li><li>'round crown'</li><li>'no crown'</li></ul> |
|
176 |
+
| 56 | <ul><li>'ultra high heel'</li><li>'mid heel'</li><li>'high heel'</li></ul> |
|
177 |
+
| 110 | <ul><li>'relaxed'</li><li>'tailored'</li></ul> |
|
178 |
+
| 47 | <ul><li>'uplifting'</li><li>'bold'</li></ul> |
|
179 |
+
| 3 | <ul><li>'changing pad'</li><li>'bottle pocket'</li></ul> |
|
180 |
+
| 0 | <ul><li>'squeeze dispenser'</li><li>'dropper'</li></ul> |
|
181 |
+
| 80 | <ul><li>'wall mount'</li><li>'ceiling mount'</li></ul> |
|
182 |
+
| 6 | <ul><li>'medium'</li><li>'wide'</li></ul> |
|
183 |
+
| 36 | <ul><li>'exterior pocket'</li><li>'exterior snap pocket'</li></ul> |
|
184 |
+
|
185 |
+
## Evaluation
|
186 |
+
|
187 |
+
### Metrics
|
188 |
+
| Label | Accuracy |
|
189 |
+
|:--------|:---------|
|
190 |
+
| **all** | 0.5493 |
|
191 |
+
|
192 |
+
## Uses
|
193 |
+
|
194 |
+
### Direct Use for Inference
|
195 |
+
|
196 |
+
First install the SetFit library:
|
197 |
+
|
198 |
+
```bash
|
199 |
+
pip install setfit
|
200 |
+
```
|
201 |
+
|
202 |
+
Then you can load this model and run inference.
|
203 |
+
|
204 |
+
```python
|
205 |
+
from setfit import SetFitModel
|
206 |
+
|
207 |
+
# Download from the 🤗 Hub
|
208 |
+
model = SetFitModel.from_pretrained("kaustubhgap/kaustubh_setfit_1iteration")
|
209 |
+
# Run inference
|
210 |
+
preds = model("tube")
|
211 |
+
```
|
212 |
+
|
213 |
+
<!--
|
214 |
+
### Downstream Use
|
215 |
+
|
216 |
+
*List how someone could finetune this model on their own dataset.*
|
217 |
+
-->
|
218 |
+
|
219 |
+
<!--
|
220 |
+
### Out-of-Scope Use
|
221 |
+
|
222 |
+
*List how the model may foreseeably be misused and address what users ought not to do with the model.*
|
223 |
+
-->
|
224 |
+
|
225 |
+
<!--
|
226 |
+
## Bias, Risks and Limitations
|
227 |
+
|
228 |
+
*What are the known or foreseeable issues stemming from this model? You could also flag here known failure cases or weaknesses of the model.*
|
229 |
+
-->
|
230 |
+
|
231 |
+
<!--
|
232 |
+
### Recommendations
|
233 |
+
|
234 |
+
*What are recommendations with respect to the foreseeable issues? For example, filtering explicit content.*
|
235 |
+
-->
|
236 |
+
|
237 |
+
## Training Details
|
238 |
+
|
239 |
+
### Training Set Metrics
|
240 |
+
| Training set | Min | Median | Max |
|
241 |
+
|:-------------|:----|:-------|:----|
|
242 |
+
| Word count | 1 | 1.7047 | 6 |
|
243 |
+
|
244 |
+
| Label | Training Sample Count |
|
245 |
+
|:------|:----------------------|
|
246 |
+
| 0 | 2 |
|
247 |
+
| 1 | 5 |
|
248 |
+
| 2 | 12 |
|
249 |
+
| 3 | 2 |
|
250 |
+
| 4 | 6 |
|
251 |
+
| 5 | 3 |
|
252 |
+
| 6 | 2 |
|
253 |
+
| 7 | 12 |
|
254 |
+
| 8 | 16 |
|
255 |
+
| 9 | 2 |
|
256 |
+
| 10 | 2 |
|
257 |
+
| 11 | 11 |
|
258 |
+
| 12 | 4 |
|
259 |
+
| 13 | 2 |
|
260 |
+
| 14 | 2 |
|
261 |
+
| 15 | 2 |
|
262 |
+
| 16 | 2 |
|
263 |
+
| 17 | 6 |
|
264 |
+
| 18 | 9 |
|
265 |
+
| 19 | 63 |
|
266 |
+
| 20 | 8 |
|
267 |
+
| 21 | 31 |
|
268 |
+
| 22 | 6 |
|
269 |
+
| 23 | 2 |
|
270 |
+
| 24 | 13 |
|
271 |
+
| 25 | 5 |
|
272 |
+
| 26 | 2 |
|
273 |
+
| 27 | 2 |
|
274 |
+
| 28 | 3 |
|
275 |
+
| 29 | 2 |
|
276 |
+
| 30 | 13 |
|
277 |
+
| 31 | 3 |
|
278 |
+
| 32 | 7 |
|
279 |
+
| 33 | 22 |
|
280 |
+
| 34 | 12 |
|
281 |
+
| 35 | 102 |
|
282 |
+
| 36 | 2 |
|
283 |
+
| 37 | 119 |
|
284 |
+
| 38 | 34 |
|
285 |
+
| 39 | 32 |
|
286 |
+
| 40 | 6 |
|
287 |
+
| 41 | 2 |
|
288 |
+
| 42 | 13 |
|
289 |
+
| 43 | 17 |
|
290 |
+
| 44 | 5 |
|
291 |
+
| 45 | 10 |
|
292 |
+
| 46 | 6 |
|
293 |
+
| 47 | 2 |
|
294 |
+
| 48 | 10 |
|
295 |
+
| 49 | 2 |
|
296 |
+
| 50 | 91 |
|
297 |
+
| 51 | 13 |
|
298 |
+
| 52 | 2 |
|
299 |
+
| 53 | 2 |
|
300 |
+
| 54 | 2 |
|
301 |
+
| 55 | 12 |
|
302 |
+
| 56 | 4 |
|
303 |
+
| 57 | 7 |
|
304 |
+
| 58 | 17 |
|
305 |
+
| 59 | 2 |
|
306 |
+
| 60 | 2 |
|
307 |
+
| 61 | 7 |
|
308 |
+
| 62 | 9 |
|
309 |
+
| 63 | 3 |
|
310 |
+
| 64 | 14 |
|
311 |
+
| 65 | 53 |
|
312 |
+
| 66 | 3 |
|
313 |
+
| 67 | 6 |
|
314 |
+
| 68 | 41 |
|
315 |
+
| 69 | 41 |
|
316 |
+
| 70 | 33 |
|
317 |
+
| 71 | 5 |
|
318 |
+
| 72 | 5 |
|
319 |
+
| 73 | 4 |
|
320 |
+
| 74 | 7 |
|
321 |
+
| 75 | 49 |
|
322 |
+
| 76 | 2 |
|
323 |
+
| 77 | 23 |
|
324 |
+
| 78 | 11 |
|
325 |
+
| 79 | 12 |
|
326 |
+
| 80 | 2 |
|
327 |
+
| 81 | 5 |
|
328 |
+
| 82 | 33 |
|
329 |
+
| 83 | 33 |
|
330 |
+
| 84 | 2 |
|
331 |
+
| 85 | 2 |
|
332 |
+
| 86 | 17 |
|
333 |
+
| 87 | 2 |
|
334 |
+
| 88 | 2 |
|
335 |
+
| 89 | 10 |
|
336 |
+
| 90 | 29 |
|
337 |
+
| 91 | 2 |
|
338 |
+
| 92 | 8 |
|
339 |
+
| 93 | 21 |
|
340 |
+
| 94 | 2 |
|
341 |
+
| 95 | 3 |
|
342 |
+
| 96 | 5 |
|
343 |
+
| 97 | 10 |
|
344 |
+
| 98 | 5 |
|
345 |
+
| 99 | 6 |
|
346 |
+
| 100 | 6 |
|
347 |
+
| 101 | 12 |
|
348 |
+
| 102 | 13 |
|
349 |
+
| 103 | 2 |
|
350 |
+
| 104 | 10 |
|
351 |
+
| 105 | 28 |
|
352 |
+
| 106 | 2 |
|
353 |
+
| 107 | 321 |
|
354 |
+
| 108 | 2 |
|
355 |
+
| 109 | 10 |
|
356 |
+
| 110 | 2 |
|
357 |
+
| 111 | 2 |
|
358 |
+
| 112 | 2 |
|
359 |
+
| 113 | 15 |
|
360 |
+
| 114 | 4 |
|
361 |
+
| 115 | 2 |
|
362 |
+
| 116 | 5 |
|
363 |
+
| 117 | 2 |
|
364 |
+
| 118 | 2 |
|
365 |
+
|
366 |
+
### Training Hyperparameters
|
367 |
+
- batch_size: (16, 16)
|
368 |
+
- num_epochs: (1, 1)
|
369 |
+
- max_steps: -1
|
370 |
+
- sampling_strategy: oversampling
|
371 |
+
- num_iterations: 10
|
372 |
+
- body_learning_rate: (2e-05, 1e-05)
|
373 |
+
- head_learning_rate: 0.01
|
374 |
+
- loss: CosineSimilarityLoss
|
375 |
+
- distance_metric: cosine_distance
|
376 |
+
- margin: 0.25
|
377 |
+
- end_to_end: False
|
378 |
+
- use_amp: False
|
379 |
+
- warmup_proportion: 0.1
|
380 |
+
- seed: 42
|
381 |
+
- eval_max_steps: -1
|
382 |
+
- load_best_model_at_end: False
|
383 |
+
|
384 |
+
### Training Results
|
385 |
+
| Epoch | Step | Training Loss | Validation Loss |
|
386 |
+
|:------:|:----:|:-------------:|:---------------:|
|
387 |
+
| 0.0004 | 1 | 0.2895 | - |
|
388 |
+
| 0.0225 | 50 | 0.2059 | - |
|
389 |
+
| 0.0449 | 100 | 0.1794 | - |
|
390 |
+
| 0.0674 | 150 | 0.1994 | - |
|
391 |
+
| 0.0898 | 200 | 0.2708 | - |
|
392 |
+
| 0.1123 | 250 | 0.1355 | - |
|
393 |
+
| 0.1347 | 300 | 0.0695 | - |
|
394 |
+
| 0.1572 | 350 | 0.117 | - |
|
395 |
+
| 0.1796 | 400 | 0.0601 | - |
|
396 |
+
| 0.2021 | 450 | 0.0873 | - |
|
397 |
+
| 0.2245 | 500 | 0.07 | - |
|
398 |
+
| 0.2470 | 550 | 0.0805 | - |
|
399 |
+
| 0.2694 | 600 | 0.0204 | - |
|
400 |
+
| 0.2919 | 650 | 0.1059 | - |
|
401 |
+
| 0.3143 | 700 | 0.1178 | - |
|
402 |
+
| 0.3368 | 750 | 0.1804 | - |
|
403 |
+
| 0.3592 | 800 | 0.0979 | - |
|
404 |
+
| 0.3817 | 850 | 0.1597 | - |
|
405 |
+
| 0.4041 | 900 | 0.1215 | - |
|
406 |
+
| 0.4266 | 950 | 0.0188 | - |
|
407 |
+
| 0.4490 | 1000 | 0.0738 | - |
|
408 |
+
| 0.4715 | 1050 | 0.0635 | - |
|
409 |
+
| 0.4939 | 1100 | 0.1439 | - |
|
410 |
+
| 0.5164 | 1150 | 0.0684 | - |
|
411 |
+
| 0.5388 | 1200 | 0.0732 | - |
|
412 |
+
| 0.5613 | 1250 | 0.0401 | - |
|
413 |
+
| 0.5837 | 1300 | 0.1223 | - |
|
414 |
+
| 0.6062 | 1350 | 0.1044 | - |
|
415 |
+
| 0.6286 | 1400 | 0.0717 | - |
|
416 |
+
| 0.6511 | 1450 | 0.0413 | - |
|
417 |
+
| 0.6736 | 1500 | 0.0544 | - |
|
418 |
+
| 0.6960 | 1550 | 0.1419 | - |
|
419 |
+
| 0.7185 | 1600 | 0.0284 | - |
|
420 |
+
| 0.7409 | 1650 | 0.0484 | - |
|
421 |
+
| 0.7634 | 1700 | 0.0049 | - |
|
422 |
+
| 0.7858 | 1750 | 0.0229 | - |
|
423 |
+
| 0.8083 | 1800 | 0.0739 | - |
|
424 |
+
| 0.8307 | 1850 | 0.0371 | - |
|
425 |
+
| 0.8532 | 1900 | 0.0213 | - |
|
426 |
+
| 0.8756 | 1950 | 0.0753 | - |
|
427 |
+
| 0.8981 | 2000 | 0.0359 | - |
|
428 |
+
| 0.9205 | 2050 | 0.0232 | - |
|
429 |
+
| 0.9430 | 2100 | 0.0507 | - |
|
430 |
+
| 0.9654 | 2150 | 0.0258 | - |
|
431 |
+
| 0.9879 | 2200 | 0.0606 | - |
|
432 |
+
| 1.0 | 2227 | - | 0.2105 |
|
433 |
+
|
434 |
+
### Framework Versions
|
435 |
+
- Python: 3.10.12
|
436 |
+
- SetFit: 1.0.3
|
437 |
+
- Sentence Transformers: 3.0.1
|
438 |
+
- Transformers: 4.36.1
|
439 |
+
- PyTorch: 2.0.1+cu118
|
440 |
+
- Datasets: 2.20.0
|
441 |
+
- Tokenizers: 0.15.0
|
442 |
+
|
443 |
+
## Citation
|
444 |
+
|
445 |
+
### BibTeX
|
446 |
+
```bibtex
|
447 |
+
@article{https://doi.org/10.48550/arxiv.2209.11055,
|
448 |
+
doi = {10.48550/ARXIV.2209.11055},
|
449 |
+
url = {https://arxiv.org/abs/2209.11055},
|
450 |
+
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
|
451 |
+
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
|
452 |
+
title = {Efficient Few-Shot Learning Without Prompts},
|
453 |
+
publisher = {arXiv},
|
454 |
+
year = {2022},
|
455 |
+
copyright = {Creative Commons Attribution 4.0 International}
|
456 |
+
}
|
457 |
+
```
|
458 |
+
|
459 |
+
<!--
|
460 |
+
## Glossary
|
461 |
+
|
462 |
+
*Clearly define terms in order to be accessible across audiences.*
|
463 |
+
-->
|
464 |
+
|
465 |
+
<!--
|
466 |
+
## Model Card Authors
|
467 |
+
|
468 |
+
*Lists the people who create the model card, providing recognition and accountability for the detailed work that goes into its construction.*
|
469 |
+
-->
|
470 |
+
|
471 |
+
<!--
|
472 |
+
## Model Card Contact
|
473 |
+
|
474 |
+
*Provides a way for people who have updates to the Model Card, suggestions, or questions, to contact the Model Card authors.*
|
475 |
+
-->
|
config.json
ADDED
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "sentence-transformers/paraphrase-mpnet-base-v2",
|
3 |
+
"architectures": [
|
4 |
+
"MPNetModel"
|
5 |
+
],
|
6 |
+
"attention_probs_dropout_prob": 0.1,
|
7 |
+
"bos_token_id": 0,
|
8 |
+
"eos_token_id": 2,
|
9 |
+
"hidden_act": "gelu",
|
10 |
+
"hidden_dropout_prob": 0.1,
|
11 |
+
"hidden_size": 768,
|
12 |
+
"initializer_range": 0.02,
|
13 |
+
"intermediate_size": 3072,
|
14 |
+
"layer_norm_eps": 1e-05,
|
15 |
+
"max_position_embeddings": 514,
|
16 |
+
"model_type": "mpnet",
|
17 |
+
"num_attention_heads": 12,
|
18 |
+
"num_hidden_layers": 12,
|
19 |
+
"pad_token_id": 1,
|
20 |
+
"relative_attention_num_buckets": 32,
|
21 |
+
"torch_dtype": "float32",
|
22 |
+
"transformers_version": "4.36.1",
|
23 |
+
"vocab_size": 30527
|
24 |
+
}
|
config_sentence_transformers.json
ADDED
@@ -0,0 +1,10 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"__version__": {
|
3 |
+
"sentence_transformers": "3.0.1",
|
4 |
+
"transformers": "4.36.1",
|
5 |
+
"pytorch": "2.0.1+cu118"
|
6 |
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},
|
7 |
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"prompts": {},
|
8 |
+
"default_prompt_name": null,
|
9 |
+
"similarity_fn_name": null
|
10 |
+
}
|
config_setfit.json
ADDED
@@ -0,0 +1,4 @@
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|
|
|
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|
|
|
|
|
1 |
+
{
|
2 |
+
"normalize_embeddings": false,
|
3 |
+
"labels": null
|
4 |
+
}
|
model.safetensors
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:35e7613963f82d98ed2072e93c29d2a955df8e41886a889b72fbb21eccc44814
|
3 |
+
size 437967672
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model_head.pkl
ADDED
@@ -0,0 +1,3 @@
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|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:5660d91ba7f83f473e68fb50c0828330ebd1a4b249b3a571198d363411323a67
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3 |
+
size 733923
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modules.json
ADDED
@@ -0,0 +1,14 @@
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|
|
|
|
|
|
1 |
+
[
|
2 |
+
{
|
3 |
+
"idx": 0,
|
4 |
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"name": "0",
|
5 |
+
"path": "",
|
6 |
+
"type": "sentence_transformers.models.Transformer"
|
7 |
+
},
|
8 |
+
{
|
9 |
+
"idx": 1,
|
10 |
+
"name": "1",
|
11 |
+
"path": "1_Pooling",
|
12 |
+
"type": "sentence_transformers.models.Pooling"
|
13 |
+
}
|
14 |
+
]
|
sentence_bert_config.json
ADDED
@@ -0,0 +1,4 @@
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"max_seq_length": 512,
|
3 |
+
"do_lower_case": false
|
4 |
+
}
|
special_tokens_map.json
ADDED
@@ -0,0 +1,51 @@
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|
1 |
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{
|
2 |
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"bos_token": {
|
3 |
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"content": "<s>",
|
4 |
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"lstrip": false,
|
5 |
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"normalized": false,
|
6 |
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"rstrip": false,
|
7 |
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"single_word": false
|
8 |
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},
|
9 |
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"cls_token": {
|
10 |
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"content": "<s>",
|
11 |
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"lstrip": false,
|
12 |
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"normalized": false,
|
13 |
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"rstrip": false,
|
14 |
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"single_word": false
|
15 |
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},
|
16 |
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"eos_token": {
|
17 |
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"content": "</s>",
|
18 |
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"lstrip": false,
|
19 |
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"normalized": false,
|
20 |
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"rstrip": false,
|
21 |
+
"single_word": false
|
22 |
+
},
|
23 |
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"mask_token": {
|
24 |
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"content": "<mask>",
|
25 |
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"lstrip": true,
|
26 |
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"normalized": false,
|
27 |
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"rstrip": false,
|
28 |
+
"single_word": false
|
29 |
+
},
|
30 |
+
"pad_token": {
|
31 |
+
"content": "<pad>",
|
32 |
+
"lstrip": false,
|
33 |
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"normalized": false,
|
34 |
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"rstrip": false,
|
35 |
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"single_word": false
|
36 |
+
},
|
37 |
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"sep_token": {
|
38 |
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"content": "</s>",
|
39 |
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"lstrip": false,
|
40 |
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"normalized": false,
|
41 |
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"rstrip": false,
|
42 |
+
"single_word": false
|
43 |
+
},
|
44 |
+
"unk_token": {
|
45 |
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"content": "[UNK]",
|
46 |
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"lstrip": false,
|
47 |
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"normalized": false,
|
48 |
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"rstrip": false,
|
49 |
+
"single_word": false
|
50 |
+
}
|
51 |
+
}
|
tokenizer.json
ADDED
The diff for this file is too large to render.
See raw diff
|
|
tokenizer_config.json
ADDED
@@ -0,0 +1,59 @@
|
|
|
|
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|
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|
1 |
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{
|
2 |
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"added_tokens_decoder": {
|
3 |
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"0": {
|
4 |
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"content": "<s>",
|
5 |
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"lstrip": false,
|
6 |
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"normalized": false,
|
7 |
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"rstrip": false,
|
8 |
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"single_word": false,
|
9 |
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"special": true
|
10 |
+
},
|
11 |
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"1": {
|
12 |
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"content": "<pad>",
|
13 |
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"lstrip": false,
|
14 |
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"normalized": false,
|
15 |
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"rstrip": false,
|
16 |
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"single_word": false,
|
17 |
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"special": true
|
18 |
+
},
|
19 |
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"2": {
|
20 |
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"content": "</s>",
|
21 |
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"lstrip": false,
|
22 |
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"normalized": false,
|
23 |
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"rstrip": false,
|
24 |
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"single_word": false,
|
25 |
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"special": true
|
26 |
+
},
|
27 |
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"104": {
|
28 |
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"content": "[UNK]",
|
29 |
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"lstrip": false,
|
30 |
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"normalized": false,
|
31 |
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"rstrip": false,
|
32 |
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"single_word": false,
|
33 |
+
"special": true
|
34 |
+
},
|
35 |
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"30526": {
|
36 |
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"content": "<mask>",
|
37 |
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"lstrip": true,
|
38 |
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"normalized": false,
|
39 |
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"rstrip": false,
|
40 |
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"single_word": false,
|
41 |
+
"special": true
|
42 |
+
}
|
43 |
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},
|
44 |
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"bos_token": "<s>",
|
45 |
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"clean_up_tokenization_spaces": true,
|
46 |
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"cls_token": "<s>",
|
47 |
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"do_basic_tokenize": true,
|
48 |
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"do_lower_case": true,
|
49 |
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"eos_token": "</s>",
|
50 |
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"mask_token": "<mask>",
|
51 |
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"model_max_length": 512,
|
52 |
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"never_split": null,
|
53 |
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"pad_token": "<pad>",
|
54 |
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"sep_token": "</s>",
|
55 |
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"strip_accents": null,
|
56 |
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"tokenize_chinese_chars": true,
|
57 |
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"tokenizer_class": "MPNetTokenizer",
|
58 |
+
"unk_token": "[UNK]"
|
59 |
+
}
|
vocab.txt
ADDED
The diff for this file is too large to render.
See raw diff
|
|