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---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_sgd_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: 0.5813953488372093
---
<!-- 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_small_sgd_0001_fold3
This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0466
- Accuracy: 0.5814
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6887 | 1.0 | 217 | 1.4610 | 0.2558 |
| 1.5962 | 2.0 | 434 | 1.3845 | 0.3488 |
| 1.5124 | 3.0 | 651 | 1.3560 | 0.3721 |
| 1.442 | 4.0 | 868 | 1.3419 | 0.3721 |
| 1.41 | 5.0 | 1085 | 1.3313 | 0.3488 |
| 1.3709 | 6.0 | 1302 | 1.3218 | 0.3721 |
| 1.3157 | 7.0 | 1519 | 1.3125 | 0.3721 |
| 1.3328 | 8.0 | 1736 | 1.3039 | 0.3488 |
| 1.3107 | 9.0 | 1953 | 1.2950 | 0.3488 |
| 1.2568 | 10.0 | 2170 | 1.2861 | 0.3488 |
| 1.2226 | 11.0 | 2387 | 1.2769 | 0.3256 |
| 1.198 | 12.0 | 2604 | 1.2671 | 0.3256 |
| 1.232 | 13.0 | 2821 | 1.2570 | 0.3488 |
| 1.1803 | 14.0 | 3038 | 1.2472 | 0.3488 |
| 1.214 | 15.0 | 3255 | 1.2376 | 0.3488 |
| 1.208 | 16.0 | 3472 | 1.2274 | 0.3953 |
| 1.1406 | 17.0 | 3689 | 1.2176 | 0.3953 |
| 1.1243 | 18.0 | 3906 | 1.2072 | 0.3953 |
| 1.1316 | 19.0 | 4123 | 1.1970 | 0.4884 |
| 1.1119 | 20.0 | 4340 | 1.1873 | 0.4884 |
| 1.117 | 21.0 | 4557 | 1.1775 | 0.5116 |
| 1.0609 | 22.0 | 4774 | 1.1681 | 0.5116 |
| 1.0751 | 23.0 | 4991 | 1.1588 | 0.5581 |
| 1.058 | 24.0 | 5208 | 1.1499 | 0.5581 |
| 1.0301 | 25.0 | 5425 | 1.1417 | 0.5581 |
| 1.089 | 26.0 | 5642 | 1.1338 | 0.5581 |
| 0.9909 | 27.0 | 5859 | 1.1255 | 0.5814 |
| 0.9932 | 28.0 | 6076 | 1.1180 | 0.5814 |
| 1.026 | 29.0 | 6293 | 1.1110 | 0.5814 |
| 1.0236 | 30.0 | 6510 | 1.1044 | 0.5814 |
| 1.0169 | 31.0 | 6727 | 1.0980 | 0.5814 |
| 1.0049 | 32.0 | 6944 | 1.0921 | 0.5814 |
| 1.0261 | 33.0 | 7161 | 1.0868 | 0.5814 |
| 0.994 | 34.0 | 7378 | 1.0819 | 0.5814 |
| 0.9887 | 35.0 | 7595 | 1.0769 | 0.5581 |
| 1.0137 | 36.0 | 7812 | 1.0725 | 0.5581 |
| 0.9359 | 37.0 | 8029 | 1.0687 | 0.5581 |
| 0.9531 | 38.0 | 8246 | 1.0651 | 0.5581 |
| 0.9682 | 39.0 | 8463 | 1.0620 | 0.5581 |
| 0.9947 | 40.0 | 8680 | 1.0590 | 0.5581 |
| 0.9063 | 41.0 | 8897 | 1.0565 | 0.5581 |
| 1.0195 | 42.0 | 9114 | 1.0543 | 0.5581 |
| 0.966 | 43.0 | 9331 | 1.0523 | 0.5581 |
| 0.9409 | 44.0 | 9548 | 1.0506 | 0.5581 |
| 0.9327 | 45.0 | 9765 | 1.0492 | 0.5581 |
| 0.9575 | 46.0 | 9982 | 1.0481 | 0.5814 |
| 0.9627 | 47.0 | 10199 | 1.0474 | 0.5814 |
| 0.9553 | 48.0 | 10416 | 1.0469 | 0.5814 |
| 0.9631 | 49.0 | 10633 | 1.0467 | 0.5814 |
| 0.944 | 50.0 | 10850 | 1.0466 | 0.5814 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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