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Vit Beans Boosted

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set: Loss: 0.0531 Accuracy: 0.9850

TipoOtherModelo basegoogle/vit-base-patch16-224-in21kVersãoRevision ae827c1Cnota

Fonte do modelo

Tipo
Other
Tamanho do arquivo
327 MB
Modelo base
google/vit-base-patch16-224-in21k
Versão
vRevision ae827c1
Atualizado
17 de set. de 2026
Downloads
5
Fonte
Hugging Face

Descrição da fonte

vit-beans-boosted

This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0531
  • Accuracy: 0.9850

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: 0.0002
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
0.76261.0330.21920.9323
0.12292.0660.16590.9323
0.11663.0990.05310.9850
0.04204.01320.05550.9850
0.02675.01650.03410.9850

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.8.5
  • Tokenizers 0.22.2

Fontes

1 fonte
Hugging FacePrimárioVersão ae827c107df0a1305873869531abd5074a6a70b9
huggingface.co/LeonSigal/vit-beans-boosted/tree/ae827c107df0a1305873869531abd5074a6a70b9

Verificado 2 de set.

Artefatos de modelo

1 artefato

model.safetensors

safetensors · 327 MB · SHA-256 60240f50dff6…94a9 · Hugging Face

Download file

Trechos de fonte

2 trechos

--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer metrics: - accuracy model-index: - name: vit-beans-boosted 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-beans-boosted This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0531 - Accuracy: 0.9850 ## 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: 0.0002 - train_batch_size: 32 - eval_batch_size: 32 - 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 - lr_scheduler_warmup_steps: 0.1 - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7626 | 1.0 | 33 | 0.2192 | 0.9323 | | 0.1229 | 2.0 | 66 | 0.1659 | 0.9323 | | 0.1166 | 3.0 | 99 | 0.0531 | 0.9850 | | 0.0420 | 4.0 | 132 | 0.0555 | 0.9850 | | 0.0267 | 5.0 | 165 | 0.0341 | 0.9850 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.8.5 - Tokenizers 0.22.2

Source context: 5 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo LeonSigal/vit-beans-boosted