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_fold3
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: 0.5695346320346321
Boya1_Adamax_1-e4_20Epoch_Deit-tiny-patch16_fold3
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: 3.5040
- Accuracy: 0.5695
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 |
|---|---|---|---|---|
| 1.3705 | 1.0 | 923 | 1.4925 | 0.4968 |
| 1.1741 | 2.0 | 1846 | 1.3247 | 0.5411 |
| 1.1089 | 3.0 | 2769 | 1.2524 | 0.5777 |
| 0.8912 | 4.0 | 3692 | 1.2699 | 0.5712 |
| 0.6118 | 5.0 | 4615 | 1.3695 | 0.5725 |
| 0.4514 | 6.0 | 5538 | 1.5162 | 0.5690 |
| 0.3342 | 7.0 | 6461 | 1.6732 | 0.5641 |
| 0.1558 | 8.0 | 7384 | 1.8402 | 0.5668 |
| 0.139 | 9.0 | 8307 | 2.0769 | 0.5676 |
| 0.0399 | 10.0 | 9230 | 2.4530 | 0.5582 |
| 0.0251 | 11.0 | 10153 | 2.6195 | 0.5630 |
| 0.0197 | 12.0 | 11076 | 2.8679 | 0.5598 |
| 0.0022 | 13.0 | 11999 | 3.0450 | 0.5593 |
| 0.0102 | 14.0 | 12922 | 3.1628 | 0.5614 |
| 0.0226 | 15.0 | 13845 | 3.2622 | 0.5655 |
| 0.0004 | 16.0 | 14768 | 3.3164 | 0.5668 |
| 0.0003 | 17.0 | 15691 | 3.3759 | 0.5703 |
| 0.0002 | 18.0 | 16614 | 3.4406 | 0.5687 |
| 0.0002 | 19.0 | 17537 | 3.4891 | 0.5695 |
| 0.0004 | 20.0 | 18460 | 3.5040 | 0.5695 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.0
- Datasets 2.19.0
- Tokenizers 0.19.1