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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_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: 0.627906976744186
---
<!-- 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_fold3
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: 2.8954
- Accuracy: 0.6279
## 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 | 1.3703 | 0.2558 |
| 1.9279 | 2.0 | 12 | 1.2966 | 0.3953 |
| 1.9279 | 3.0 | 18 | 1.5490 | 0.3256 |
| 1.3451 | 4.0 | 24 | 1.3082 | 0.4186 |
| 1.2763 | 5.0 | 30 | 1.4000 | 0.3023 |
| 1.2763 | 6.0 | 36 | 1.3783 | 0.3488 |
| 1.1541 | 7.0 | 42 | 1.2878 | 0.3953 |
| 1.1541 | 8.0 | 48 | 1.2528 | 0.4651 |
| 1.0831 | 9.0 | 54 | 1.2761 | 0.4884 |
| 1.0032 | 10.0 | 60 | 0.9439 | 0.6279 |
| 1.0032 | 11.0 | 66 | 1.9597 | 0.3256 |
| 1.0649 | 12.0 | 72 | 1.3501 | 0.4651 |
| 1.0649 | 13.0 | 78 | 1.2845 | 0.6279 |
| 0.8485 | 14.0 | 84 | 1.2102 | 0.5814 |
| 0.7758 | 15.0 | 90 | 1.5993 | 0.4651 |
| 0.7758 | 16.0 | 96 | 1.1744 | 0.6279 |
| 0.5906 | 17.0 | 102 | 1.9493 | 0.4884 |
| 0.5906 | 18.0 | 108 | 1.3370 | 0.5581 |
| 0.5433 | 19.0 | 114 | 1.8704 | 0.5814 |
| 0.4053 | 20.0 | 120 | 2.3449 | 0.6047 |
| 0.4053 | 21.0 | 126 | 2.8071 | 0.4651 |
| 0.6321 | 22.0 | 132 | 1.8750 | 0.5814 |
| 0.6321 | 23.0 | 138 | 1.9591 | 0.5814 |
| 0.2883 | 24.0 | 144 | 2.0517 | 0.6744 |
| 0.2248 | 25.0 | 150 | 2.2716 | 0.5581 |
| 0.2248 | 26.0 | 156 | 2.5758 | 0.5581 |
| 0.0908 | 27.0 | 162 | 2.4971 | 0.5814 |
| 0.0908 | 28.0 | 168 | 2.2990 | 0.6512 |
| 0.0607 | 29.0 | 174 | 2.2806 | 0.6977 |
| 0.0385 | 30.0 | 180 | 2.4187 | 0.6279 |
| 0.0385 | 31.0 | 186 | 2.4113 | 0.6744 |
| 0.0085 | 32.0 | 192 | 2.4630 | 0.6512 |
| 0.0085 | 33.0 | 198 | 2.7214 | 0.6279 |
| 0.004 | 34.0 | 204 | 2.8415 | 0.6047 |
| 0.0007 | 35.0 | 210 | 2.8858 | 0.6047 |
| 0.0007 | 36.0 | 216 | 2.8956 | 0.6279 |
| 0.0005 | 37.0 | 222 | 2.8935 | 0.6279 |
| 0.0005 | 38.0 | 228 | 2.8908 | 0.6279 |
| 0.0004 | 39.0 | 234 | 2.8922 | 0.6279 |
| 0.0003 | 40.0 | 240 | 2.8936 | 0.6279 |
| 0.0003 | 41.0 | 246 | 2.8951 | 0.6279 |
| 0.0003 | 42.0 | 252 | 2.8954 | 0.6279 |
| 0.0003 | 43.0 | 258 | 2.8954 | 0.6279 |
| 0.0003 | 44.0 | 264 | 2.8954 | 0.6279 |
| 0.0003 | 45.0 | 270 | 2.8954 | 0.6279 |
| 0.0003 | 46.0 | 276 | 2.8954 | 0.6279 |
| 0.0003 | 47.0 | 282 | 2.8954 | 0.6279 |
| 0.0003 | 48.0 | 288 | 2.8954 | 0.6279 |
| 0.0003 | 49.0 | 294 | 2.8954 | 0.6279 |
| 0.0003 | 50.0 | 300 | 2.8954 | 0.6279 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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