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My Awesome Food Model

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: 2.2741 Accuracy: 0.464

TipoOtherModelo basegoogle/vit-base-patch16-224-in21kVersiónRevision eb2989cBcalidad

Fuente del modelo

Tipo
Other
Tamaño del archivo
328 MB
Modelo base
google/vit-base-patch16-224-in21k
Versión
vRevision eb2989c
Actualizado
22 sept 2026
Descargas
4
Fuente
Hugging Face

Extracto de la fuente

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: 2.2741 Accuracy: 0.464

Fuentes

1 fuente
Hugging FacePrincipalVersión eb2989c0c45712b2c74fcd5125d5a3f8cde82cdd
huggingface.co/nimishac28/my_awesome_food_model/tree/eb2989c0c45712b2c74fcd5125d5a3f8cde82cdd

Verificado 27 ago

Artefactos del modelo

1 artefacto

model.safetensors

safetensors · 328 MB · SHA-256 4abc6e06aaf6…c9a9 · Hugging Face

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Extractos de fuentes

2 extractos

--- library_name: transformers license: apache-2.0 base_model: google/vit-base-patch16-224-in21k tags: - trackio - trackio:https://huggingface.co/spaces/nimishac28/huggingface-static-2f2526 - generated_from_trainer metrics: - accuracy model-index: - name: my_awesome_food_model results: [] --- <a href="https://huggingface.co/spaces/nimishac28/huggingface-static-2f2526" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a> <!-- 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. --> # my_awesome_food_model 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: 2.2741 - Accuracy: 0.464 ## 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: 16 - eval_batch_size: 16 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - 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: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 2.9399 | 1.0 | 63 | 2.8394 | 0.362 | | 2.5064 | 2.0 | 126 | 2.4431 | 0.428 | | 2.3115 | 3.0 | 189 | 2.2741 | 0.464 | ### Framework versions - Transformers 5.12.1 - Pytorch 2.11.0+cu128 - Datasets 4.0.0 - Tokenizers 0.22.2

Source context: 4 downloads · 0 likes · Pipeline image-classification · Library transformers · Repo nimishac28/my_awesome_food_model