metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-base-oxford-iiit-pets
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: WillyArdiyanto/12-cat-breed-OxfordIIIT
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8333333333333334
vit-base-oxford-iiit-pets
This model is a fine-tuned version of google/vit-base-patch16-224 on the WillyArdiyanto/12-cat-breed-OxfordIIIT dataset. It achieves the following results on the evaluation set:
- Loss: 0.6488
- Accuracy: 0.8333
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: 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 |
|---|---|---|---|---|
| No log | 1.0 | 60 | 1.1640 | 0.7917 |
| 1.4196 | 2.0 | 120 | 0.7480 | 0.9 |
| 1.4196 | 3.0 | 180 | 0.5855 | 0.9417 |
| 0.6321 | 4.0 | 240 | 0.5252 | 0.9417 |
| 0.4886 | 5.0 | 300 | 0.5078 | 0.9417 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1