|
--- |
|
license: apache-2.0 |
|
tags: |
|
- image-classification |
|
- generated_from_trainer |
|
datasets: |
|
- snacks |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: vit-snacks |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: Matthijs/snacks |
|
type: snacks |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.9392670157068063 |
|
--- |
|
|
|
<!-- 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-snacks |
|
|
|
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 Matthijs/snacks dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2754 |
|
- Accuracy: 0.9393 |
|
|
|
## Model description |
|
|
|
upload any image of your fave yummy snack |
|
|
|
## Intended uses & limitations |
|
|
|
there are only 20 different varieties of snacks |
|
|
|
## 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: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 5 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.8724 | 0.33 | 100 | 0.9118 | 0.8670 | |
|
| 0.5628 | 0.66 | 200 | 0.6873 | 0.8471 | |
|
| 0.4421 | 0.99 | 300 | 0.4995 | 0.8691 | |
|
| 0.2837 | 1.32 | 400 | 0.4008 | 0.9026 | |
|
| 0.1645 | 1.65 | 500 | 0.3702 | 0.9058 | |
|
| 0.1604 | 1.98 | 600 | 0.3981 | 0.8921 | |
|
| 0.0498 | 2.31 | 700 | 0.3185 | 0.9204 | |
|
| 0.0406 | 2.64 | 800 | 0.3427 | 0.9141 | |
|
| 0.1049 | 2.97 | 900 | 0.3444 | 0.9173 | |
|
| 0.0272 | 3.3 | 1000 | 0.3168 | 0.9246 | |
|
| 0.0186 | 3.63 | 1100 | 0.3142 | 0.9288 | |
|
| 0.0203 | 3.96 | 1200 | 0.2931 | 0.9298 | |
|
| 0.007 | 4.29 | 1300 | 0.2754 | 0.9393 | |
|
| 0.0072 | 4.62 | 1400 | 0.2778 | 0.9403 | |
|
| 0.0073 | 4.95 | 1500 | 0.2782 | 0.9393 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.20.1 |
|
- Pytorch 1.11.0+cu113 |
|
- Datasets 2.3.2 |
|
- Tokenizers 0.12.1 |
|
|
