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Ft Vilt B32 Mlm

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

KindOtherBase modeldandelin/vilt-b32-mlmVersionRevision 60dffa8

Model source

Kind
Other
File size
430 MB
Base model
dandelin/vilt-b32-mlm
Version
vRevision 60dffa8
Updated
Sep 25, 2026
Downloads
17
Tasks
Captioning
Source
Hugging Face

Source description

ft-vilt-b32-mlm

This model is a fine-tuned version of dandelin/vilt-b32-mlm on the vqa 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: 8
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20
  • mixed_precision_training: Native AMP

Training results

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.0.0
  • Datasets 2.15.0
  • Tokenizers 0.15.0

Sources

1 source
Hugging FacePrimaryVersion 60dffa801a7f871726beb8da5782243d7105d108
huggingface.co/aisuko/ft-vilt-b32-mlm/tree/60dffa801a7f871726beb8da5782243d7105d108

Verified Sep 11

Model artifacts

1 artifact

model.safetensors

safetensors · 430 MB · SHA-256 07af0b7f8e8e…53a6 · Hugging Face

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Source excerpts

2 excerpts

--- license: apache-2.0 base_model: dandelin/vilt-b32-mlm tags: - generated_from_trainer datasets: - vqa model-index: - name: ft-vilt-b32-mlm 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. --> # ft-vilt-b32-mlm This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-mlm) on the vqa 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: 8 - eval_batch_size: 16 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 20 - mixed_precision_training: Native AMP ### Training results ### Framework versions - Transformers 4.35.2 - Pytorch 2.0.0 - Datasets 2.15.0 - Tokenizers 0.15.0

Source context: 17 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo aisuko/ft-vilt-b32-mlm