metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- fruits
- vegetables
- food
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: less-augmentation-fruits-and-vegetables-vit
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: less-augmentation-fruits-and-vegetables-vit
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9303621169916435
less-augmentation-fruits-and-vegetables-vit
This model is a fine-tuned version of google/vit-base-patch16-224 on the less-augmentation-fruits-and-vegetables-vit dataset. It achieves the following results on the evaluation set:
- Loss: 0.2129
- Accuracy: 0.9304
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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.809 | 1.0 | 195 | 0.2873 | 0.9145 |
| 0.5755 | 2.0 | 390 | 0.2350 | 0.9202 |
| 0.5052 | 3.0 | 585 | 0.2173 | 0.9145 |
| 0.4884 | 4.0 | 780 | 0.2104 | 0.9288 |
| 0.4518 | 5.0 | 975 | 0.2079 | 0.9288 |
Framework versions
- Transformers 4.50.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1