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---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_tiny_adamax_0001_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: 0.9069767441860465
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hushem_40x_deit_tiny_adamax_0001_fold3
This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8703
- Accuracy: 0.9070
## 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: 32
- eval_batch_size: 32
- 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0405 | 1.0 | 217 | 0.7475 | 0.8372 |
| 0.0174 | 2.0 | 434 | 0.3741 | 0.8837 |
| 0.0347 | 3.0 | 651 | 0.7246 | 0.8605 |
| 0.0 | 4.0 | 868 | 0.4948 | 0.9070 |
| 0.0001 | 5.0 | 1085 | 0.5865 | 0.8837 |
| 0.0 | 6.0 | 1302 | 0.7334 | 0.8837 |
| 0.0 | 7.0 | 1519 | 0.7116 | 0.8837 |
| 0.0 | 8.0 | 1736 | 0.7193 | 0.8837 |
| 0.0 | 9.0 | 1953 | 0.7217 | 0.8837 |
| 0.0 | 10.0 | 2170 | 0.7267 | 0.9070 |
| 0.0 | 11.0 | 2387 | 0.7322 | 0.9070 |
| 0.0 | 12.0 | 2604 | 0.7327 | 0.9070 |
| 0.0 | 13.0 | 2821 | 0.7378 | 0.9070 |
| 0.0 | 14.0 | 3038 | 0.7396 | 0.9070 |
| 0.0 | 15.0 | 3255 | 0.7467 | 0.9070 |
| 0.0 | 16.0 | 3472 | 0.7473 | 0.9070 |
| 0.0 | 17.0 | 3689 | 0.7591 | 0.9070 |
| 0.0 | 18.0 | 3906 | 0.7633 | 0.9070 |
| 0.0 | 19.0 | 4123 | 0.7713 | 0.9070 |
| 0.0 | 20.0 | 4340 | 0.7767 | 0.9070 |
| 0.0 | 21.0 | 4557 | 0.7800 | 0.9070 |
| 0.0 | 22.0 | 4774 | 0.7902 | 0.9070 |
| 0.0 | 23.0 | 4991 | 0.7915 | 0.9070 |
| 0.0 | 24.0 | 5208 | 0.8041 | 0.9070 |
| 0.0 | 25.0 | 5425 | 0.8046 | 0.9070 |
| 0.0 | 26.0 | 5642 | 0.8231 | 0.8837 |
| 0.0 | 27.0 | 5859 | 0.8344 | 0.8837 |
| 0.0 | 28.0 | 6076 | 0.8309 | 0.8837 |
| 0.0 | 29.0 | 6293 | 0.8419 | 0.8837 |
| 0.0 | 30.0 | 6510 | 0.8453 | 0.8837 |
| 0.0 | 31.0 | 6727 | 0.8681 | 0.8837 |
| 0.0 | 32.0 | 6944 | 0.8660 | 0.8837 |
| 0.0 | 33.0 | 7161 | 0.8697 | 0.8837 |
| 0.0 | 34.0 | 7378 | 0.8846 | 0.8837 |
| 0.0 | 35.0 | 7595 | 0.8902 | 0.8837 |
| 0.0 | 36.0 | 7812 | 0.8974 | 0.8837 |
| 0.0 | 37.0 | 8029 | 0.8857 | 0.8837 |
| 0.0 | 38.0 | 8246 | 0.8854 | 0.8837 |
| 0.0 | 39.0 | 8463 | 0.8857 | 0.8837 |
| 0.0 | 40.0 | 8680 | 0.8940 | 0.8837 |
| 0.0 | 41.0 | 8897 | 0.8956 | 0.8837 |
| 0.0 | 42.0 | 9114 | 0.8901 | 0.8837 |
| 0.0 | 43.0 | 9331 | 0.8853 | 0.9070 |
| 0.0 | 44.0 | 9548 | 0.8877 | 0.8837 |
| 0.0 | 45.0 | 9765 | 0.8928 | 0.9070 |
| 0.0 | 46.0 | 9982 | 0.8951 | 0.9070 |
| 0.0 | 47.0 | 10199 | 0.8786 | 0.9070 |
| 0.0 | 48.0 | 10416 | 0.8807 | 0.9070 |
| 0.0 | 49.0 | 10633 | 0.8732 | 0.9070 |
| 0.0 | 50.0 | 10850 | 0.8703 | 0.9070 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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