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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: smids_1x_deit_small_adamax_001_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: 0.8566666666666667
---
<!-- 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_1x_deit_small_adamax_001_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: 1.1786
- Accuracy: 0.8567
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6005 | 1.0 | 75 | 0.4146 | 0.83 |
| 0.4739 | 2.0 | 150 | 0.5214 | 0.7783 |
| 0.3159 | 3.0 | 225 | 0.3979 | 0.8467 |
| 0.3044 | 4.0 | 300 | 0.4320 | 0.845 |
| 0.3525 | 5.0 | 375 | 0.3215 | 0.8817 |
| 0.1872 | 6.0 | 450 | 0.4978 | 0.8267 |
| 0.2467 | 7.0 | 525 | 0.5551 | 0.8 |
| 0.1504 | 8.0 | 600 | 0.5301 | 0.8367 |
| 0.1309 | 9.0 | 675 | 0.5781 | 0.84 |
| 0.2177 | 10.0 | 750 | 0.5269 | 0.865 |
| 0.0844 | 11.0 | 825 | 0.5112 | 0.865 |
| 0.0758 | 12.0 | 900 | 0.6543 | 0.8617 |
| 0.1176 | 13.0 | 975 | 0.5860 | 0.855 |
| 0.0455 | 14.0 | 1050 | 0.7995 | 0.8317 |
| 0.0687 | 15.0 | 1125 | 0.6395 | 0.8633 |
| 0.0296 | 16.0 | 1200 | 0.8580 | 0.8517 |
| 0.0214 | 17.0 | 1275 | 0.9274 | 0.85 |
| 0.0164 | 18.0 | 1350 | 0.8318 | 0.8733 |
| 0.0192 | 19.0 | 1425 | 0.9491 | 0.8567 |
| 0.0338 | 20.0 | 1500 | 0.7653 | 0.8567 |
| 0.0007 | 21.0 | 1575 | 0.9985 | 0.8517 |
| 0.0001 | 22.0 | 1650 | 0.9967 | 0.87 |
| 0.0156 | 23.0 | 1725 | 1.1459 | 0.85 |
| 0.0033 | 24.0 | 1800 | 1.1111 | 0.8517 |
| 0.005 | 25.0 | 1875 | 1.1114 | 0.8467 |
| 0.0195 | 26.0 | 1950 | 1.0184 | 0.8617 |
| 0.0001 | 27.0 | 2025 | 1.0582 | 0.8567 |
| 0.0022 | 28.0 | 2100 | 1.1162 | 0.86 |
| 0.0 | 29.0 | 2175 | 1.1193 | 0.86 |
| 0.0 | 30.0 | 2250 | 1.1254 | 0.8567 |
| 0.0 | 31.0 | 2325 | 1.1372 | 0.86 |
| 0.0016 | 32.0 | 2400 | 1.1758 | 0.8583 |
| 0.0051 | 33.0 | 2475 | 1.1778 | 0.845 |
| 0.0047 | 34.0 | 2550 | 1.0600 | 0.8667 |
| 0.01 | 35.0 | 2625 | 1.1195 | 0.855 |
| 0.0037 | 36.0 | 2700 | 1.1381 | 0.8533 |
| 0.0025 | 37.0 | 2775 | 1.1434 | 0.855 |
| 0.0 | 38.0 | 2850 | 1.1612 | 0.8583 |
| 0.0 | 39.0 | 2925 | 1.1652 | 0.8567 |
| 0.0 | 40.0 | 3000 | 1.1711 | 0.855 |
| 0.0 | 41.0 | 3075 | 1.1589 | 0.86 |
| 0.0028 | 42.0 | 3150 | 1.1617 | 0.8617 |
| 0.0032 | 43.0 | 3225 | 1.1622 | 0.86 |
| 0.0 | 44.0 | 3300 | 1.1672 | 0.86 |
| 0.0027 | 45.0 | 3375 | 1.1668 | 0.86 |
| 0.0026 | 46.0 | 3450 | 1.1710 | 0.86 |
| 0.0057 | 47.0 | 3525 | 1.1686 | 0.86 |
| 0.0 | 48.0 | 3600 | 1.1767 | 0.8567 |
| 0.0 | 49.0 | 3675 | 1.1760 | 0.8583 |
| 0.0044 | 50.0 | 3750 | 1.1786 | 0.8567 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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