FaceDataset
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: 0.0251 Accuracy: 0.9909 Precision: 0.9909 Recall: 0.9909...
Fonte do modelo
- Tipo
- Other
- Tamanho do arquivo
- 327 MB
- Modelo base
- google/vit-base-patch16-224-in21k
- Versão
- vRevision 0c81bc4
- Atualizado
- 11 de out. de 2026
- Publicador
- @Pauloherrera1
- Downloads
- 9
- Fonte
- Hugging Face
Descrição da fonte
FaceDataset
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: 0.0251
- Accuracy: 0.9909
- Precision: 0.9909
- Recall: 0.9909
- F1: 0.9909
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: 16
- eval_batch_size: 16
- 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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.1021 | 1.0 | 243 | 0.0957 | 0.9781 | 0.9790 | 0.9781 | 0.9780 |
| 0.0457 | 2.0 | 486 | 0.0271 | 0.9909 | 0.9910 | 0.9909 | 0.9909 |
| 0.0191 | 3.0 | 729 | 0.0414 | 0.9872 | 0.9872 | 0.9872 | 0.9872 |
| 0.0082 | 4.0 | 972 | 0.0251 | 0.9909 | 0.9909 | 0.9909 | 0.9909 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
Fontes
1 fonte
Fontes
1 fonteVerificado 6 de ago.
Artefatos de modelo
1 artefato
Artefatos de modelo
1 artefatoTrechos de fonte
3 trechos
Trechos de fonte
3 trechos--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - generated_from_trainer metrics: - accuracy - precision - recall - f1 model-index: - name: FaceDataset 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. --> # FaceDataset 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: 0.0251 - Accuracy: 0.9909 - Precision: 0.9909 - Recall: 0.9909 - F1: 0.9909 ## 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: 16 - eval_batch_size: 16 - 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: 4 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| | 0.1021 | 1.0 | 243 | 0.0957 | 0.9781 | 0.9790 | 0.9781 | 0.9780 | | 0.0457 | 2.0 | 486 | 0.0271 | 0.9909 | 0.9910 | 0.9909 | 0.9909 | | 0.0191 | 3.0 | 729 | 0.0414 | 0.9872 | 0.9872 | 0.9872 | 0.9872 | | 0.0082 | 4.0 | 972 | 0.0251 | 0.9909 | 0.9909 | 0.9909 | 0.9909 | ### Framework versions - Transformers 5.0.0 - Pytorch 2.10.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2
Source context: 9 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo Pauloherrera1/FaceDataset
Source context: 2 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo Pauloherrera1/FaceDataset
