metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: Boya1_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold4
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.5623306233062331
Boya1_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold4
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 3.5379
- Accuracy: 0.5623
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4184 | 1.0 | 923 | 1.5125 | 0.4894 |
| 1.1581 | 2.0 | 1846 | 1.3440 | 0.5398 |
| 1.0675 | 3.0 | 2769 | 1.2921 | 0.5683 |
| 0.9984 | 4.0 | 3692 | 1.3169 | 0.5756 |
| 0.6437 | 5.0 | 4615 | 1.3971 | 0.5629 |
| 0.491 | 6.0 | 5538 | 1.5307 | 0.5547 |
| 0.3697 | 7.0 | 6461 | 1.6679 | 0.5615 |
| 0.2372 | 8.0 | 7384 | 1.9476 | 0.5461 |
| 0.0824 | 9.0 | 8307 | 2.1631 | 0.5531 |
| 0.0471 | 10.0 | 9230 | 2.4822 | 0.5485 |
| 0.0645 | 11.0 | 10153 | 2.7301 | 0.5523 |
| 0.0461 | 12.0 | 11076 | 2.8827 | 0.5588 |
| 0.0021 | 13.0 | 11999 | 3.1615 | 0.5575 |
| 0.0011 | 14.0 | 12922 | 3.1796 | 0.5612 |
| 0.0141 | 15.0 | 13845 | 3.2737 | 0.5566 |
| 0.0004 | 16.0 | 14768 | 3.3570 | 0.5593 |
| 0.0004 | 17.0 | 15691 | 3.4150 | 0.5621 |
| 0.0003 | 18.0 | 16614 | 3.4800 | 0.5615 |
| 0.0002 | 19.0 | 17537 | 3.5180 | 0.5615 |
| 0.0002 | 20.0 | 18460 | 3.5379 | 0.5623 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1