Skip to content
ModelListedExternal
Download

Graphcorevqa

This model is a fine-tuned version of dandelin/vilt-b32-mlm on the None dataset.

KindOtherBase modeldandelin/vilt-b32-mlmVersionRevision 976b3fb

Model source

Kind
Other
File size
431 MB
Base model
dandelin/vilt-b32-mlm
Version
vRevision 976b3fb
Updated
Sep 25, 2026
Downloads
18
Tasks
Captioning
Source
Hugging Face

Source description

graphcorevqa

This model is a fine-tuned version of dandelin/vilt-b32-mlm on the None 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: 20

Training results

Framework versions

  • Transformers 4.33.2
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.5
  • Tokenizers 0.13.3

Sources

1 source
Hugging FacePrimaryVersion 976b3fb6791537851a2b0d8595df00dace3d382b
huggingface.co/VinayReddyPulyala/graphcorevqa/tree/976b3fb6791537851a2b0d8595df00dace3d382b

Verified Sep 11

Model artifacts

1 artifact

pytorch_model.bin

bin · 431 MB · SHA-256 ea23ebee5f36…3bbe · Hugging Face

Download

Source excerpts

2 excerpts

--- license: apache-2.0 base_model: dandelin/vilt-b32-mlm tags: - generated_from_trainer model-index: - name: graphcorevqa 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. --> # graphcorevqa This model is a fine-tuned version of [dandelin/vilt-b32-mlm](https://huggingface.co/dandelin/vilt-b32-mlm) on the None 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: 20 ### Training results ### Framework versions - Transformers 4.33.2 - Pytorch 2.0.1+cu118 - Datasets 2.14.5 - Tokenizers 0.13.3

Source context: 18 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo VinayReddyPulyala/graphcorevqa