Vit Base Patch16 224
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset.
Source du modèle
- Type
- Other
- Taille du fichier
- 330 MB
- Modèle de base
- google/vit-base-patch16-224
- Version
- vRevision 9413da7
- Mis à jour
- 22 oct. 2026
- Téléchargements
- 4
- Source
- Hugging Face
Description de la source
vit-base-patch16-224
This model is a fine-tuned version of google/vit-base-patch16-224 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: 8
- 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: 3.0
Framework versions
- Transformers 5.12.1
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2
Sources
1 source
Sources
1 sourceVérifié 22 oct.
Artefacts du modèle
1 artefact
Artefacts du modèle
1 artefactExtraits de sources
3 extraits
Extraits de sources
3 extraits--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224 tags: - generated_from_trainer model-index: - name: vit-base-patch16-224 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. --> # vit-base-patch16-224 This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) 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: 8 - 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: 3.0 ### Framework versions - Transformers 5.12.1 - Pytorch 2.12.0+cu130 - Datasets 5.0.0 - Tokenizers 0.22.2
Source context: 4 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo swadhindas324/vit-base-patch16-224
Source context: 12 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo swadhindas324/vit-base-patch16-224
