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Vit Base Patch16 224

This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset.

TypeOtherModèle de basegoogle/vit-base-patch16-224VersionRevision 9413da7BClasse

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
Hugging FacePrincipalVersion 9413da72a492fd9f7992ab5bd1a2562d3f1a040c
huggingface.co/swadhindas324/vit-base-patch16-224/tree/9413da72a492fd9f7992ab5bd1a2562d3f1a040c

Vérifié 22 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 330 MB · SHA-256 b975663f08e1…8157 · Hugging Face

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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