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Vilt Finetuned 200

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

KindOtherBase modeldandelin/vilt-b32-mlmVersionRevision 9eb5b4f

Model source

Kind
Other
File size
431 MB
Base model
dandelin/vilt-b32-mlm
Version
vRevision 9eb5b4f
Updated
Sep 26, 2026
Downloads
15
Tasks
Captioning
Source
Hugging Face

Source description

vilt_finetuned_200

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: 16
  • eval_batch_size: 32
  • 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 4.34.0
  • Pytorch 2.1.0a0+29c30b1
  • Datasets 2.14.5
  • Tokenizers 0.14.1

Sources

1 source
Hugging FacePrimaryVersion 9eb5b4f34b691cefd5c52d51700750cdae31dca1
huggingface.co/schubertcarvalho/vilt_finetuned_200/tree/9eb5b4f34b691cefd5c52d51700750cdae31dca1

Verified Sep 11

Model artifacts

1 artifact

pytorch_model.bin

bin · 431 MB · SHA-256 d1b7fd586ad7…9e82 · Hugging Face

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Source excerpts

2 excerpts

--- license: apache-2.0 base_model: dandelin/vilt-b32-mlm tags: - vilt-vqa-200 - generated_from_trainer datasets: - vqa model-index: - name: vilt_finetuned_200 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_200 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: 16 - eval_batch_size: 32 - 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 4.34.0 - Pytorch 2.1.0a0+29c30b1 - Datasets 2.14.5 - Tokenizers 0.14.1

Source context: 15 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo schubertcarvalho/vilt_finetuned_200