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My Vqa Model

This model is a fine-tuned version of dandelin/vilt-b32-mlm on an unknown dataset.

TipoOtherModelo basedandelin/vilt-b32-mlmVersãoRevision e9735aaCnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
431 MB
Modelo base
dandelin/vilt-b32-mlm
Versão
vRevision e9735aa
Atualizado
23 de out. de 2026
Downloads
3
Fonte
Hugging Face

Descrição da fonte

my_vqa_model

This model is a fine-tuned version of dandelin/vilt-b32-mlm on an unknown 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 20

Framework versions

  • Transformers 4.56.1
  • Pytorch 2.8.0+cu126
  • Datasets 4.0.0
  • Tokenizers 0.22.0

Fontes

1 fonte
Hugging FacePrimárioVersão e9735aab10c5aec36bb8afbab44a001b5afb62ad
huggingface.co/Maria-pro/my_vqa_model/tree/e9735aab10c5aec36bb8afbab44a001b5afb62ad

Verificado 23 de out.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 431 MB · SHA-256 3a83c236853f…39e6 · Hugging Face

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Trechos de fonte

3 trechos

--- library_name: transformers license: apache-2.0 base_model: dandelin/vilt-b32-mlm tags: - generated_from_trainer model-index: - name: my_vqa_model 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. --> # my_vqa_model This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-mlm) on an unknown 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 20 ### Framework versions - Transformers 4.56.1 - Pytorch 2.8.0+cu126 - Datasets 4.0.0 - Tokenizers 0.22.0

Source context: 3 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo Maria-pro/my_vqa_model

Source context: 4 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo Maria-pro/my_vqa_model