metadata
license: apache-2.0
base_model: WinKawaks/vit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: vit-tiny-patch16-224-winkawaks
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.842911877394636
vit-tiny-patch16-224-winkawaks
This model is a fine-tuned version of WinKawaks/vit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3542
- Accuracy: 0.8429
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5345 | 1.0 | 202 | 0.4689 | 0.7771 |
| 0.4936 | 2.0 | 404 | 0.5022 | 0.7485 |
| 0.4911 | 3.0 | 606 | 0.3887 | 0.8279 |
| 0.4191 | 4.0 | 808 | 0.4121 | 0.8098 |
| 0.4408 | 5.0 | 1010 | 0.3897 | 0.8255 |
| 0.4134 | 6.0 | 1212 | 0.3714 | 0.8332 |
| 0.4117 | 7.0 | 1414 | 0.3685 | 0.8377 |
| 0.3991 | 8.0 | 1616 | 0.3602 | 0.8412 |
| 0.3936 | 9.0 | 1818 | 0.3542 | 0.8429 |
| 0.3422 | 10.0 | 2020 | 0.3540 | 0.8398 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2