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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_001_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: 0.5853658536585366
---
<!-- 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_001_fold5
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: 2.9089
- Accuracy: 0.5854
## 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: 0.001
- 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 | 1.5709 | 0.2683 |
| 1.6365 | 2.0 | 12 | 1.3231 | 0.3171 |
| 1.6365 | 3.0 | 18 | 1.0858 | 0.4878 |
| 1.2777 | 4.0 | 24 | 1.0527 | 0.4634 |
| 1.0819 | 5.0 | 30 | 2.4025 | 0.4878 |
| 1.0819 | 6.0 | 36 | 1.0776 | 0.6098 |
| 1.1957 | 7.0 | 42 | 1.2491 | 0.4878 |
| 1.1957 | 8.0 | 48 | 1.2390 | 0.4878 |
| 1.0582 | 9.0 | 54 | 2.4696 | 0.3659 |
| 0.9645 | 10.0 | 60 | 0.9800 | 0.6585 |
| 0.9645 | 11.0 | 66 | 1.4465 | 0.4878 |
| 0.7158 | 12.0 | 72 | 1.3709 | 0.4146 |
| 0.7158 | 13.0 | 78 | 1.8787 | 0.5610 |
| 0.4707 | 14.0 | 84 | 2.2003 | 0.4878 |
| 0.3746 | 15.0 | 90 | 2.7652 | 0.4390 |
| 0.3746 | 16.0 | 96 | 1.4738 | 0.6098 |
| 0.3815 | 17.0 | 102 | 2.1297 | 0.4878 |
| 0.3815 | 18.0 | 108 | 2.7358 | 0.4634 |
| 0.2562 | 19.0 | 114 | 2.1602 | 0.6341 |
| 0.215 | 20.0 | 120 | 2.4495 | 0.5122 |
| 0.215 | 21.0 | 126 | 2.2161 | 0.5366 |
| 0.0855 | 22.0 | 132 | 2.6756 | 0.5610 |
| 0.0855 | 23.0 | 138 | 3.4355 | 0.5366 |
| 0.0976 | 24.0 | 144 | 2.8453 | 0.6098 |
| 0.0588 | 25.0 | 150 | 2.9043 | 0.5854 |
| 0.0588 | 26.0 | 156 | 3.0589 | 0.4878 |
| 0.0051 | 27.0 | 162 | 2.7256 | 0.6098 |
| 0.0051 | 28.0 | 168 | 2.6655 | 0.6098 |
| 0.0018 | 29.0 | 174 | 2.6795 | 0.6098 |
| 0.005 | 30.0 | 180 | 2.7568 | 0.6098 |
| 0.005 | 31.0 | 186 | 2.8042 | 0.6098 |
| 0.0004 | 32.0 | 192 | 2.8224 | 0.6098 |
| 0.0004 | 33.0 | 198 | 2.8428 | 0.6098 |
| 0.0002 | 34.0 | 204 | 2.8628 | 0.5854 |
| 0.0002 | 35.0 | 210 | 2.8783 | 0.5854 |
| 0.0002 | 36.0 | 216 | 2.8881 | 0.5854 |
| 0.0002 | 37.0 | 222 | 2.8950 | 0.5854 |
| 0.0002 | 38.0 | 228 | 2.9002 | 0.5854 |
| 0.0002 | 39.0 | 234 | 2.9045 | 0.5854 |
| 0.0002 | 40.0 | 240 | 2.9071 | 0.5854 |
| 0.0002 | 41.0 | 246 | 2.9084 | 0.5854 |
| 0.0001 | 42.0 | 252 | 2.9089 | 0.5854 |
| 0.0001 | 43.0 | 258 | 2.9089 | 0.5854 |
| 0.0002 | 44.0 | 264 | 2.9089 | 0.5854 |
| 0.0001 | 45.0 | 270 | 2.9089 | 0.5854 |
| 0.0001 | 46.0 | 276 | 2.9089 | 0.5854 |
| 0.0002 | 47.0 | 282 | 2.9089 | 0.5854 |
| 0.0002 | 48.0 | 288 | 2.9089 | 0.5854 |
| 0.0001 | 49.0 | 294 | 2.9089 | 0.5854 |
| 0.0001 | 50.0 | 300 | 2.9089 | 0.5854 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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