Vilt Finetuned Fashion Vqa
This model is a fine-tuned version of dandelin/vilt-b32-finetuned-vqa on the generator dataset.
Fuente del modelo
- Tipo
- Other
- Tamaño del archivo
- 431 MB
- Modelo base
- dandelin/vilt-b32-finetuned-vqa
- Versión
- vRevision a8771d8
- Actualizado
- 26 sept 2026
- Descargas
- 20
- Tareas
- Descripción
- Fuente
- Hugging Face
Descripción de la fuente
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
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 11 sept
Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactoExtractos de fuentes
2 extractos
Extractos de fuentes
2 extractos--- 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
