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---
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_deit_base_sgd_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: 0.39
---
<!-- 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. -->
# smids_3x_deit_base_sgd_00001_fold5
This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0839
- Accuracy: 0.39
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.1036 | 1.0 | 225 | 1.1105 | 0.345 |
| 1.1373 | 2.0 | 450 | 1.1092 | 0.3483 |
| 1.1157 | 3.0 | 675 | 1.1081 | 0.345 |
| 1.0955 | 4.0 | 900 | 1.1069 | 0.345 |
| 1.1099 | 5.0 | 1125 | 1.1058 | 0.3467 |
| 1.1089 | 6.0 | 1350 | 1.1047 | 0.345 |
| 1.1067 | 7.0 | 1575 | 1.1037 | 0.35 |
| 1.0974 | 8.0 | 1800 | 1.1027 | 0.3483 |
| 1.103 | 9.0 | 2025 | 1.1017 | 0.3483 |
| 1.0886 | 10.0 | 2250 | 1.1008 | 0.35 |
| 1.1042 | 11.0 | 2475 | 1.0999 | 0.3467 |
| 1.0817 | 12.0 | 2700 | 1.0990 | 0.3483 |
| 1.0974 | 13.0 | 2925 | 1.0981 | 0.35 |
| 1.0843 | 14.0 | 3150 | 1.0973 | 0.3533 |
| 1.0853 | 15.0 | 3375 | 1.0965 | 0.3567 |
| 1.0875 | 16.0 | 3600 | 1.0957 | 0.355 |
| 1.101 | 17.0 | 3825 | 1.0950 | 0.3517 |
| 1.0772 | 18.0 | 4050 | 1.0943 | 0.3533 |
| 1.0926 | 19.0 | 4275 | 1.0936 | 0.355 |
| 1.1029 | 20.0 | 4500 | 1.0929 | 0.3567 |
| 1.0868 | 21.0 | 4725 | 1.0923 | 0.3567 |
| 1.0978 | 22.0 | 4950 | 1.0917 | 0.3617 |
| 1.0872 | 23.0 | 5175 | 1.0911 | 0.3633 |
| 1.0922 | 24.0 | 5400 | 1.0905 | 0.3717 |
| 1.0864 | 25.0 | 5625 | 1.0900 | 0.3717 |
| 1.0678 | 26.0 | 5850 | 1.0895 | 0.3733 |
| 1.0684 | 27.0 | 6075 | 1.0890 | 0.3767 |
| 1.0793 | 28.0 | 6300 | 1.0885 | 0.3767 |
| 1.0972 | 29.0 | 6525 | 1.0881 | 0.38 |
| 1.0711 | 30.0 | 6750 | 1.0877 | 0.38 |
| 1.0882 | 31.0 | 6975 | 1.0873 | 0.3783 |
| 1.0634 | 32.0 | 7200 | 1.0869 | 0.38 |
| 1.0851 | 33.0 | 7425 | 1.0865 | 0.3783 |
| 1.0775 | 34.0 | 7650 | 1.0862 | 0.38 |
| 1.0604 | 35.0 | 7875 | 1.0859 | 0.3783 |
| 1.0657 | 36.0 | 8100 | 1.0856 | 0.38 |
| 1.0791 | 37.0 | 8325 | 1.0854 | 0.3817 |
| 1.0734 | 38.0 | 8550 | 1.0851 | 0.3817 |
| 1.0719 | 39.0 | 8775 | 1.0849 | 0.3867 |
| 1.0762 | 40.0 | 9000 | 1.0847 | 0.3883 |
| 1.074 | 41.0 | 9225 | 1.0846 | 0.3883 |
| 1.0744 | 42.0 | 9450 | 1.0844 | 0.3883 |
| 1.0769 | 43.0 | 9675 | 1.0843 | 0.3883 |
| 1.079 | 44.0 | 9900 | 1.0842 | 0.3883 |
| 1.0661 | 45.0 | 10125 | 1.0841 | 0.3883 |
| 1.0565 | 46.0 | 10350 | 1.0840 | 0.3883 |
| 1.071 | 47.0 | 10575 | 1.0840 | 0.3883 |
| 1.0641 | 48.0 | 10800 | 1.0839 | 0.39 |
| 1.0708 | 49.0 | 11025 | 1.0839 | 0.39 |
| 1.0689 | 50.0 | 11250 | 1.0839 | 0.39 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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