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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: food101-vit-base-patch16-224-in21k
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. -->
# food101-vit-base-patch16-224-in21k
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3853
- Accuracy: 0.908
## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8312 | 1.0 | 9469 | 0.6893 | 0.8576 |
| 0.6401 | 2.0 | 18938 | 0.4571 | 0.8784 |
| 0.7021 | 3.0 | 28407 | 0.4081 | 0.8905 |
| 0.8365 | 4.0 | 37876 | 0.3962 | 0.8946 |
| 0.3562 | 5.0 | 47345 | 0.3932 | 0.8954 |
| 0.3552 | 6.0 | 56814 | 0.3876 | 0.9004 |
| 0.3962 | 7.0 | 66283 | 0.3854 | 0.9049 |
| 0.4242 | 8.0 | 75752 | 0.3865 | 0.9066 |
| 0.2785 | 9.0 | 85221 | 0.3867 | 0.9070 |
| 0.3446 | 10.0 | 94690 | 0.3853 | 0.908 |
### Framework versions
- Transformers 4.38.0
- Pytorch 2.1.2+cu118
- Datasets 2.19.1
- Tokenizers 0.15.2
|