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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_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: 0.5777777777777777
---
<!-- 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_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: 3.0653
- Accuracy: 0.5778
## 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 | 1.5866 | 0.2444 |
| 1.9023 | 2.0 | 12 | 1.3764 | 0.2444 |
| 1.9023 | 3.0 | 18 | 1.3051 | 0.4222 |
| 1.349 | 4.0 | 24 | 1.1457 | 0.4889 |
| 1.2765 | 5.0 | 30 | 1.1296 | 0.5333 |
| 1.2765 | 6.0 | 36 | 1.0799 | 0.4667 |
| 0.9532 | 7.0 | 42 | 0.9251 | 0.5778 |
| 0.9532 | 8.0 | 48 | 0.9697 | 0.6 |
| 0.606 | 9.0 | 54 | 1.3926 | 0.4889 |
| 0.572 | 10.0 | 60 | 1.7732 | 0.5778 |
| 0.572 | 11.0 | 66 | 1.3882 | 0.5556 |
| 0.5961 | 12.0 | 72 | 1.7835 | 0.5333 |
| 0.5961 | 13.0 | 78 | 1.6876 | 0.5111 |
| 0.36 | 14.0 | 84 | 2.6292 | 0.5556 |
| 0.1021 | 15.0 | 90 | 3.3955 | 0.4444 |
| 0.1021 | 16.0 | 96 | 2.7199 | 0.5333 |
| 0.0705 | 17.0 | 102 | 3.2188 | 0.5778 |
| 0.0705 | 18.0 | 108 | 2.9572 | 0.5778 |
| 0.1408 | 19.0 | 114 | 3.4311 | 0.6222 |
| 0.0481 | 20.0 | 120 | 3.3680 | 0.5111 |
| 0.0481 | 21.0 | 126 | 3.9440 | 0.4889 |
| 0.0285 | 22.0 | 132 | 3.0805 | 0.5111 |
| 0.0285 | 23.0 | 138 | 3.2788 | 0.4889 |
| 0.0077 | 24.0 | 144 | 3.3798 | 0.5111 |
| 0.0144 | 25.0 | 150 | 3.3118 | 0.5333 |
| 0.0144 | 26.0 | 156 | 3.1251 | 0.5111 |
| 0.0005 | 27.0 | 162 | 2.9134 | 0.5778 |
| 0.0005 | 28.0 | 168 | 2.8352 | 0.6 |
| 0.0006 | 29.0 | 174 | 2.7529 | 0.5778 |
| 0.0002 | 30.0 | 180 | 2.8235 | 0.6 |
| 0.0002 | 31.0 | 186 | 2.8802 | 0.6 |
| 0.0001 | 32.0 | 192 | 2.9253 | 0.5778 |
| 0.0001 | 33.0 | 198 | 2.9651 | 0.5778 |
| 0.0001 | 34.0 | 204 | 2.9943 | 0.5778 |
| 0.0001 | 35.0 | 210 | 3.0146 | 0.5778 |
| 0.0001 | 36.0 | 216 | 3.0314 | 0.5778 |
| 0.0001 | 37.0 | 222 | 3.0446 | 0.5778 |
| 0.0001 | 38.0 | 228 | 3.0538 | 0.5778 |
| 0.0001 | 39.0 | 234 | 3.0596 | 0.5778 |
| 0.0001 | 40.0 | 240 | 3.0631 | 0.5778 |
| 0.0001 | 41.0 | 246 | 3.0649 | 0.5778 |
| 0.0001 | 42.0 | 252 | 3.0653 | 0.5778 |
| 0.0001 | 43.0 | 258 | 3.0653 | 0.5778 |
| 0.0001 | 44.0 | 264 | 3.0653 | 0.5778 |
| 0.0001 | 45.0 | 270 | 3.0653 | 0.5778 |
| 0.0001 | 46.0 | 276 | 3.0653 | 0.5778 |
| 0.0001 | 47.0 | 282 | 3.0653 | 0.5778 |
| 0.0001 | 48.0 | 288 | 3.0653 | 0.5778 |
| 0.0001 | 49.0 | 294 | 3.0653 | 0.5778 |
| 0.0001 | 50.0 | 300 | 3.0653 | 0.5778 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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