metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: deit-base
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: vuongnhathien/30VNFoods
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8398809523809524
deit-base
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the vuongnhathien/30VNFoods dataset. It achieves the following results on the evaluation set:
- Loss: 0.7340
- Accuracy: 0.8399
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: 0.0005
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9389 | 1.0 | 275 | 0.9157 | 0.7268 |
| 0.5942 | 2.0 | 550 | 0.8308 | 0.7622 |
| 0.3701 | 3.0 | 825 | 0.7638 | 0.7873 |
| 0.2164 | 4.0 | 1100 | 0.8891 | 0.7825 |
| 0.1215 | 5.0 | 1375 | 0.8665 | 0.7932 |
| 0.0563 | 6.0 | 1650 | 0.8048 | 0.8215 |
| 0.0169 | 7.0 | 1925 | 0.7529 | 0.8370 |
| 0.0068 | 8.0 | 2200 | 0.7177 | 0.8505 |
| 0.0032 | 9.0 | 2475 | 0.6994 | 0.8533 |
| 0.0036 | 10.0 | 2750 | 0.6989 | 0.8529 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2