|
--- |
|
license: apache-2.0 |
|
base_model: google/vit-base-patch16-224-in21k |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- food101 |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vit-base-patch16-224-in21k-food101-24-12 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: food101 |
|
type: food101 |
|
config: default |
|
split: validation |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9068514851485149 |
|
--- |
|
|
|
<!-- 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-in21k-food101-24-12 |
|
|
|
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: 0.3533 |
|
- Accuracy: 0.9069 |
|
|
|
## 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: 24 |
|
- eval_batch_size: 24 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 96 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 12 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 2.7927 | 1.0 | 789 | 2.5629 | 0.7693 | |
|
| 1.256 | 2.0 | 1578 | 0.9637 | 0.8583 | |
|
| 0.94 | 3.0 | 2367 | 0.5866 | 0.8816 | |
|
| 0.6693 | 4.0 | 3157 | 0.4752 | 0.8888 | |
|
| 0.6337 | 5.0 | 3946 | 0.4282 | 0.8941 | |
|
| 0.5811 | 6.0 | 4735 | 0.4110 | 0.8949 | |
|
| 0.4661 | 7.0 | 5524 | 0.3875 | 0.8990 | |
|
| 0.4188 | 8.0 | 6314 | 0.3776 | 0.9010 | |
|
| 0.5045 | 9.0 | 7103 | 0.3633 | 0.9049 | |
|
| 0.3437 | 10.0 | 7892 | 0.3611 | 0.9058 | |
|
| 0.3494 | 11.0 | 8681 | 0.3568 | 0.9060 | |
|
| 0.3381 | 12.0 | 9468 | 0.3533 | 0.9069 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.14.6 |
|
- Tokenizers 0.14.1 |
|
|
