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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_1x_deit_small_adamax_0001_fold2
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: 0.6
---
<!-- 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_1x_deit_small_adamax_0001_fold2
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: 2.0748
- Accuracy: 0.6
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.2729 | 0.4 |
| 1.2121 | 2.0 | 12 | 1.1250 | 0.6222 |
| 1.2121 | 3.0 | 18 | 1.2362 | 0.5556 |
| 0.4291 | 4.0 | 24 | 1.2042 | 0.6444 |
| 0.1116 | 5.0 | 30 | 1.1861 | 0.6 |
| 0.1116 | 6.0 | 36 | 1.6632 | 0.5556 |
| 0.0196 | 7.0 | 42 | 1.7499 | 0.6 |
| 0.0196 | 8.0 | 48 | 1.7915 | 0.5556 |
| 0.0051 | 9.0 | 54 | 1.8168 | 0.5778 |
| 0.0016 | 10.0 | 60 | 1.8187 | 0.6222 |
| 0.0016 | 11.0 | 66 | 1.8480 | 0.6222 |
| 0.0008 | 12.0 | 72 | 1.8621 | 0.6222 |
| 0.0008 | 13.0 | 78 | 1.8730 | 0.6222 |
| 0.0006 | 14.0 | 84 | 1.8908 | 0.6222 |
| 0.0005 | 15.0 | 90 | 1.9136 | 0.6222 |
| 0.0005 | 16.0 | 96 | 1.9335 | 0.6222 |
| 0.0004 | 17.0 | 102 | 1.9501 | 0.6222 |
| 0.0004 | 18.0 | 108 | 1.9655 | 0.6222 |
| 0.0004 | 19.0 | 114 | 1.9783 | 0.6222 |
| 0.0003 | 20.0 | 120 | 1.9900 | 0.6222 |
| 0.0003 | 21.0 | 126 | 1.9990 | 0.6222 |
| 0.0003 | 22.0 | 132 | 2.0067 | 0.6222 |
| 0.0003 | 23.0 | 138 | 2.0139 | 0.6 |
| 0.0003 | 24.0 | 144 | 2.0208 | 0.6 |
| 0.0003 | 25.0 | 150 | 2.0271 | 0.6 |
| 0.0003 | 26.0 | 156 | 2.0322 | 0.6 |
| 0.0003 | 27.0 | 162 | 2.0367 | 0.6 |
| 0.0003 | 28.0 | 168 | 2.0419 | 0.6 |
| 0.0003 | 29.0 | 174 | 2.0471 | 0.6 |
| 0.0003 | 30.0 | 180 | 2.0520 | 0.6 |
| 0.0003 | 31.0 | 186 | 2.0560 | 0.6 |
| 0.0002 | 32.0 | 192 | 2.0593 | 0.6 |
| 0.0002 | 33.0 | 198 | 2.0621 | 0.6 |
| 0.0003 | 34.0 | 204 | 2.0649 | 0.6 |
| 0.0003 | 35.0 | 210 | 2.0672 | 0.6 |
| 0.0003 | 36.0 | 216 | 2.0692 | 0.6 |
| 0.0002 | 37.0 | 222 | 2.0710 | 0.6 |
| 0.0002 | 38.0 | 228 | 2.0723 | 0.6 |
| 0.0002 | 39.0 | 234 | 2.0735 | 0.6 |
| 0.0002 | 40.0 | 240 | 2.0742 | 0.6 |
| 0.0002 | 41.0 | 246 | 2.0747 | 0.6 |
| 0.0002 | 42.0 | 252 | 2.0748 | 0.6 |
| 0.0002 | 43.0 | 258 | 2.0748 | 0.6 |
| 0.0002 | 44.0 | 264 | 2.0748 | 0.6 |
| 0.0002 | 45.0 | 270 | 2.0748 | 0.6 |
| 0.0002 | 46.0 | 276 | 2.0748 | 0.6 |
| 0.0002 | 47.0 | 282 | 2.0748 | 0.6 |
| 0.0002 | 48.0 | 288 | 2.0748 | 0.6 |
| 0.0002 | 49.0 | 294 | 2.0748 | 0.6 |
| 0.0002 | 50.0 | 300 | 2.0748 | 0.6 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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