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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_1x_deit_tiny_adamax_00001_fold5
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: 0.5121951219512195
---
<!-- 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_tiny_adamax_00001_fold5
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: 0.9982
- Accuracy: 0.5122
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.3816 | 0.2927 |
| 1.4331 | 2.0 | 12 | 1.3595 | 0.2195 |
| 1.4331 | 3.0 | 18 | 1.3006 | 0.2927 |
| 1.2071 | 4.0 | 24 | 1.2477 | 0.3415 |
| 1.0931 | 5.0 | 30 | 1.2218 | 0.3659 |
| 1.0931 | 6.0 | 36 | 1.1904 | 0.3415 |
| 0.9583 | 7.0 | 42 | 1.2070 | 0.3659 |
| 0.9583 | 8.0 | 48 | 1.1804 | 0.3415 |
| 0.875 | 9.0 | 54 | 1.1663 | 0.3415 |
| 0.7821 | 10.0 | 60 | 1.1729 | 0.3659 |
| 0.7821 | 11.0 | 66 | 1.1600 | 0.3659 |
| 0.7082 | 12.0 | 72 | 1.1535 | 0.3659 |
| 0.7082 | 13.0 | 78 | 1.1283 | 0.3902 |
| 0.5865 | 14.0 | 84 | 1.1050 | 0.4146 |
| 0.5549 | 15.0 | 90 | 1.0989 | 0.4146 |
| 0.5549 | 16.0 | 96 | 1.0902 | 0.4146 |
| 0.4748 | 17.0 | 102 | 1.0889 | 0.4146 |
| 0.4748 | 18.0 | 108 | 1.0670 | 0.4146 |
| 0.4005 | 19.0 | 114 | 1.0529 | 0.4146 |
| 0.3717 | 20.0 | 120 | 1.0514 | 0.4146 |
| 0.3717 | 21.0 | 126 | 1.0589 | 0.4146 |
| 0.3189 | 22.0 | 132 | 1.0546 | 0.4146 |
| 0.3189 | 23.0 | 138 | 1.0253 | 0.4390 |
| 0.2768 | 24.0 | 144 | 1.0205 | 0.4390 |
| 0.2632 | 25.0 | 150 | 1.0386 | 0.4146 |
| 0.2632 | 26.0 | 156 | 1.0297 | 0.4390 |
| 0.2284 | 27.0 | 162 | 1.0322 | 0.4634 |
| 0.2284 | 28.0 | 168 | 1.0102 | 0.4634 |
| 0.196 | 29.0 | 174 | 1.0015 | 0.4878 |
| 0.1861 | 30.0 | 180 | 1.0070 | 0.4634 |
| 0.1861 | 31.0 | 186 | 1.0149 | 0.4878 |
| 0.1711 | 32.0 | 192 | 1.0173 | 0.4878 |
| 0.1711 | 33.0 | 198 | 1.0083 | 0.4878 |
| 0.1508 | 34.0 | 204 | 1.0068 | 0.5122 |
| 0.1433 | 35.0 | 210 | 0.9998 | 0.5122 |
| 0.1433 | 36.0 | 216 | 0.9984 | 0.5122 |
| 0.1371 | 37.0 | 222 | 0.9985 | 0.5122 |
| 0.1371 | 38.0 | 228 | 0.9983 | 0.5122 |
| 0.1311 | 39.0 | 234 | 0.9983 | 0.5122 |
| 0.1245 | 40.0 | 240 | 0.9977 | 0.5122 |
| 0.1245 | 41.0 | 246 | 0.9980 | 0.5122 |
| 0.1273 | 42.0 | 252 | 0.9982 | 0.5122 |
| 0.1273 | 43.0 | 258 | 0.9982 | 0.5122 |
| 0.1185 | 44.0 | 264 | 0.9982 | 0.5122 |
| 0.1259 | 45.0 | 270 | 0.9982 | 0.5122 |
| 0.1259 | 46.0 | 276 | 0.9982 | 0.5122 |
| 0.1239 | 47.0 | 282 | 0.9982 | 0.5122 |
| 0.1239 | 48.0 | 288 | 0.9982 | 0.5122 |
| 0.1264 | 49.0 | 294 | 0.9982 | 0.5122 |
| 0.1234 | 50.0 | 300 | 0.9982 | 0.5122 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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