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Vilt Finetuned Fashion Vqa

This model is a fine-tuned version of dandelin/vilt-b32-finetuned-vqa on the generator dataset.

TipoOtherModelo basedandelin/vilt-b32-finetuned-vqaVersãoRevision a8771d8

Fonte do modelo

Tipo
Other
Tamanho do arquivo
431 MB
Modelo base
dandelin/vilt-b32-finetuned-vqa
Versão
vRevision a8771d8
Atualizado
26 de set. de 2026
Downloads
20
Tarefas
Legendas
Fonte
Hugging Face

Descrição da fonte

vilt-finetuned-fashion-vqa

This model is a fine-tuned version of dandelin/vilt-b32-finetuned-vqa on the generator dataset.

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: 5e-05
  • train_batch_size: 4
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3

Training results

Framework versions

  • Transformers 4.34.1
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1

Fontes

1 fonte
Hugging FacePrimárioVersão a8771d8fdd9d65853e1e653d9a61fdc506e319b1
huggingface.co/jalbrechts/vilt-finetuned-fashion-vqa/tree/a8771d8fdd9d65853e1e653d9a61fdc506e319b1

Verificado 11 de set.

Artefatos de modelo

1 artefato

pytorch_model.bin

bin · 431 MB · SHA-256 62d273312f3a…2b5d · Hugging Face

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Trechos de fonte

2 trechos

--- license: apache-2.0 base_model: dandelin/vilt-b32-finetuned-vqa tags: - generated_from_trainer datasets: - generator model-index: - name: vilt-finetuned-fashion-vqa results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # vilt-finetuned-fashion-vqa This model is a fine-tuned version of [dandelin/vilt-b32-finetuned-vqa](https://huggingface.co/dandelin/vilt-b32-finetuned-vqa) on the generator dataset. ## 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: 5e-05 - train_batch_size: 4 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.6 - Tokenizers 0.14.1

Source context: 20 downloads · 1 likes · Pipeline visual-question-answering · Library transformers · Repo jalbrechts/vilt-finetuned-fashion-vqa