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DistilBERT Finetuned Resumes Sections

has-abi

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distilBERT-finetuned-resumes-sections This model is a fine-tuned version of Geotrend/distilbert-base-en-fr-cased on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.0369 F1: 0.9652 Roc Auc: 0.9808 Accuracy: 0.9621 Model description More information needed Intended uses & limitations More information needed Training and evaluation data More information needed Training procedure Training hyperparameters The following hyperparameters were used during training: learning_rate: 2e-05 train_batch_size: 8 eval_batch_size: 8 seed: 42 optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 lr_scheduler_type: linear num_epochs: 20 Training results Framework versions Transformers 4.21.1 Pytorch 1.12.1+cu113 Datasets 2.4.0 Tokenizers 0.12.1
text-classification

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Creator Models

ModelCostRuns
Bert Finetuned Resumes Sections$?18
Extended_distilBERT Finetuned Resumes Sections$?359

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Overview

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Creatorhas-abi
Model NameDistilBERT Finetuned Resumes Sections
Description

distilBERT-finetuned-resumes-sections This model is a fine-...

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Tagstext-classification
Model LinkView on HuggingFace
API SpecView on HuggingFace
Github LinkNo Github link provided
Paper LinkNo paper link provided

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Runs3,597
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Cost per Run$-
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