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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_rms_00001_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: 0.9285714285714286
---
<!-- 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_rms_00001_fold4
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: 0.4229
- Accuracy: 0.9286
## 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: 1e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.1412 | 1.0 | 219 | 0.1610 | 0.9286 |
| 0.013 | 2.0 | 438 | 0.1553 | 0.9524 |
| 0.0005 | 3.0 | 657 | 0.1135 | 0.9762 |
| 0.0002 | 4.0 | 876 | 0.2956 | 0.9286 |
| 0.0001 | 5.0 | 1095 | 0.1278 | 0.9762 |
| 0.0 | 6.0 | 1314 | 0.2416 | 0.9286 |
| 0.0031 | 7.0 | 1533 | 0.2692 | 0.9286 |
| 0.0 | 8.0 | 1752 | 0.1088 | 0.9524 |
| 0.0 | 9.0 | 1971 | 0.1134 | 0.9524 |
| 0.0 | 10.0 | 2190 | 0.1607 | 0.9524 |
| 0.0 | 11.0 | 2409 | 0.2098 | 0.9524 |
| 0.0 | 12.0 | 2628 | 0.2244 | 0.9524 |
| 0.0 | 13.0 | 2847 | 0.2259 | 0.9524 |
| 0.0 | 14.0 | 3066 | 0.2811 | 0.9524 |
| 0.0 | 15.0 | 3285 | 0.3300 | 0.9524 |
| 0.0 | 16.0 | 3504 | 0.3199 | 0.9524 |
| 0.0 | 17.0 | 3723 | 0.3615 | 0.9524 |
| 0.0 | 18.0 | 3942 | 0.4872 | 0.9524 |
| 0.0 | 19.0 | 4161 | 0.4327 | 0.9524 |
| 0.0 | 20.0 | 4380 | 0.4099 | 0.9524 |
| 0.0 | 21.0 | 4599 | 0.4211 | 0.9524 |
| 0.0 | 22.0 | 4818 | 0.3019 | 0.9524 |
| 0.0 | 23.0 | 5037 | 0.3473 | 0.9524 |
| 0.0 | 24.0 | 5256 | 0.3822 | 0.9524 |
| 0.0 | 25.0 | 5475 | 0.4512 | 0.9524 |
| 0.0 | 26.0 | 5694 | 0.3963 | 0.9524 |
| 0.0 | 27.0 | 5913 | 0.5056 | 0.9524 |
| 0.0 | 28.0 | 6132 | 0.4587 | 0.9524 |
| 0.0 | 29.0 | 6351 | 0.4379 | 0.9524 |
| 0.0 | 30.0 | 6570 | 0.4500 | 0.9524 |
| 0.0 | 31.0 | 6789 | 0.4166 | 0.9524 |
| 0.0 | 32.0 | 7008 | 0.3798 | 0.9524 |
| 0.0 | 33.0 | 7227 | 0.4566 | 0.9524 |
| 0.0 | 34.0 | 7446 | 0.3959 | 0.9524 |
| 0.0 | 35.0 | 7665 | 0.3429 | 0.9524 |
| 0.0 | 36.0 | 7884 | 0.3690 | 0.9524 |
| 0.0 | 37.0 | 8103 | 0.4056 | 0.9524 |
| 0.0 | 38.0 | 8322 | 0.4315 | 0.9286 |
| 0.0 | 39.0 | 8541 | 0.4336 | 0.9286 |
| 0.0 | 40.0 | 8760 | 0.4561 | 0.9524 |
| 0.0 | 41.0 | 8979 | 0.4723 | 0.9286 |
| 0.0 | 42.0 | 9198 | 0.3818 | 0.9286 |
| 0.0 | 43.0 | 9417 | 0.4220 | 0.9286 |
| 0.0 | 44.0 | 9636 | 0.4298 | 0.9286 |
| 0.0 | 45.0 | 9855 | 0.4315 | 0.9286 |
| 0.0 | 46.0 | 10074 | 0.4212 | 0.9286 |
| 0.0 | 47.0 | 10293 | 0.4170 | 0.9286 |
| 0.0 | 48.0 | 10512 | 0.4294 | 0.9286 |
| 0.0 | 49.0 | 10731 | 0.4253 | 0.9286 |
| 0.0 | 50.0 | 10950 | 0.4229 | 0.9286 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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