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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_001_fold4
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: 0.6190476190476191
---
<!-- 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_001_fold4
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: 2.7093
- Accuracy: 0.6190
## 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 | 1.4186 | 0.2619 |
| 1.7828 | 2.0 | 12 | 1.5668 | 0.2381 |
| 1.7828 | 3.0 | 18 | 1.3464 | 0.2619 |
| 1.4289 | 4.0 | 24 | 1.2387 | 0.2857 |
| 1.3071 | 5.0 | 30 | 1.0086 | 0.5952 |
| 1.3071 | 6.0 | 36 | 1.1662 | 0.3333 |
| 1.1964 | 7.0 | 42 | 1.2853 | 0.4286 |
| 1.1964 | 8.0 | 48 | 1.2187 | 0.3333 |
| 1.0152 | 9.0 | 54 | 0.8730 | 0.6190 |
| 0.7906 | 10.0 | 60 | 0.9343 | 0.5714 |
| 0.7906 | 11.0 | 66 | 1.6411 | 0.5 |
| 0.5517 | 12.0 | 72 | 2.1397 | 0.3095 |
| 0.5517 | 13.0 | 78 | 1.0282 | 0.5476 |
| 0.856 | 14.0 | 84 | 1.1613 | 0.4762 |
| 0.4273 | 15.0 | 90 | 1.2606 | 0.5476 |
| 0.4273 | 16.0 | 96 | 1.4223 | 0.5952 |
| 0.2649 | 17.0 | 102 | 1.5904 | 0.6429 |
| 0.2649 | 18.0 | 108 | 2.3346 | 0.5714 |
| 0.1584 | 19.0 | 114 | 2.4890 | 0.5476 |
| 0.1352 | 20.0 | 120 | 2.2551 | 0.5476 |
| 0.1352 | 21.0 | 126 | 1.7877 | 0.5714 |
| 0.1303 | 22.0 | 132 | 2.3533 | 0.5714 |
| 0.1303 | 23.0 | 138 | 2.3850 | 0.5714 |
| 0.0457 | 24.0 | 144 | 2.3656 | 0.6667 |
| 0.0031 | 25.0 | 150 | 2.3202 | 0.6190 |
| 0.0031 | 26.0 | 156 | 2.4368 | 0.6667 |
| 0.0014 | 27.0 | 162 | 2.5601 | 0.6429 |
| 0.0014 | 28.0 | 168 | 2.6475 | 0.6667 |
| 0.0004 | 29.0 | 174 | 2.7011 | 0.6667 |
| 0.0002 | 30.0 | 180 | 2.7227 | 0.6429 |
| 0.0002 | 31.0 | 186 | 2.7312 | 0.6429 |
| 0.0002 | 32.0 | 192 | 2.7259 | 0.6429 |
| 0.0002 | 33.0 | 198 | 2.7193 | 0.6429 |
| 0.0001 | 34.0 | 204 | 2.7128 | 0.6429 |
| 0.0001 | 35.0 | 210 | 2.7095 | 0.6429 |
| 0.0001 | 36.0 | 216 | 2.7084 | 0.6429 |
| 0.0001 | 37.0 | 222 | 2.7078 | 0.6429 |
| 0.0001 | 38.0 | 228 | 2.7079 | 0.6429 |
| 0.0001 | 39.0 | 234 | 2.7085 | 0.6429 |
| 0.0001 | 40.0 | 240 | 2.7091 | 0.6190 |
| 0.0001 | 41.0 | 246 | 2.7093 | 0.6190 |
| 0.0001 | 42.0 | 252 | 2.7093 | 0.6190 |
| 0.0001 | 43.0 | 258 | 2.7093 | 0.6190 |
| 0.0001 | 44.0 | 264 | 2.7093 | 0.6190 |
| 0.0001 | 45.0 | 270 | 2.7093 | 0.6190 |
| 0.0001 | 46.0 | 276 | 2.7093 | 0.6190 |
| 0.0001 | 47.0 | 282 | 2.7093 | 0.6190 |
| 0.0001 | 48.0 | 288 | 2.7093 | 0.6190 |
| 0.0001 | 49.0 | 294 | 2.7093 | 0.6190 |
| 0.0001 | 50.0 | 300 | 2.7093 | 0.6190 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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