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---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_beit_base_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: 0.4523809523809524
---
<!-- 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_beit_base_adamax_001_fold4
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3503
- Accuracy: 0.4524
## 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 | 1.4229 | 0.2381 |
| 2.0151 | 2.0 | 12 | 1.3893 | 0.2619 |
| 2.0151 | 3.0 | 18 | 1.3408 | 0.3333 |
| 1.3963 | 4.0 | 24 | 1.3326 | 0.3095 |
| 1.3169 | 5.0 | 30 | 1.2412 | 0.4762 |
| 1.3169 | 6.0 | 36 | 1.0247 | 0.5476 |
| 1.2588 | 7.0 | 42 | 1.2101 | 0.3571 |
| 1.2588 | 8.0 | 48 | 1.0013 | 0.5238 |
| 1.1685 | 9.0 | 54 | 1.3288 | 0.4524 |
| 1.1624 | 10.0 | 60 | 1.0173 | 0.5 |
| 1.1624 | 11.0 | 66 | 1.2213 | 0.4762 |
| 1.163 | 12.0 | 72 | 1.3131 | 0.4286 |
| 1.163 | 13.0 | 78 | 1.0794 | 0.5238 |
| 1.0128 | 14.0 | 84 | 1.2744 | 0.3810 |
| 1.1156 | 15.0 | 90 | 1.2253 | 0.5 |
| 1.1156 | 16.0 | 96 | 1.2674 | 0.4048 |
| 0.9374 | 17.0 | 102 | 1.1623 | 0.4524 |
| 0.9374 | 18.0 | 108 | 1.5694 | 0.4048 |
| 0.9149 | 19.0 | 114 | 1.0570 | 0.5476 |
| 0.912 | 20.0 | 120 | 1.2919 | 0.4286 |
| 0.912 | 21.0 | 126 | 1.4307 | 0.5 |
| 0.6869 | 22.0 | 132 | 1.5771 | 0.5238 |
| 0.6869 | 23.0 | 138 | 2.1692 | 0.3571 |
| 0.6883 | 24.0 | 144 | 1.5822 | 0.5714 |
| 0.7288 | 25.0 | 150 | 2.0687 | 0.4524 |
| 0.7288 | 26.0 | 156 | 2.1992 | 0.4524 |
| 0.4823 | 27.0 | 162 | 2.2715 | 0.5238 |
| 0.4823 | 28.0 | 168 | 3.3968 | 0.4286 |
| 0.4173 | 29.0 | 174 | 2.2538 | 0.5476 |
| 0.4253 | 30.0 | 180 | 3.6242 | 0.3810 |
| 0.4253 | 31.0 | 186 | 2.4386 | 0.5952 |
| 0.3088 | 32.0 | 192 | 3.2728 | 0.4762 |
| 0.3088 | 33.0 | 198 | 3.5241 | 0.5476 |
| 0.1666 | 34.0 | 204 | 3.5230 | 0.5 |
| 0.2645 | 35.0 | 210 | 3.7888 | 0.4286 |
| 0.2645 | 36.0 | 216 | 4.2240 | 0.5238 |
| 0.1416 | 37.0 | 222 | 4.2393 | 0.5 |
| 0.1416 | 38.0 | 228 | 4.0612 | 0.4762 |
| 0.1169 | 39.0 | 234 | 4.3686 | 0.4524 |
| 0.0781 | 40.0 | 240 | 4.2437 | 0.4762 |
| 0.0781 | 41.0 | 246 | 4.2703 | 0.4286 |
| 0.06 | 42.0 | 252 | 4.3503 | 0.4524 |
| 0.06 | 43.0 | 258 | 4.3503 | 0.4524 |
| 0.0264 | 44.0 | 264 | 4.3503 | 0.4524 |
| 0.1093 | 45.0 | 270 | 4.3503 | 0.4524 |
| 0.1093 | 46.0 | 276 | 4.3503 | 0.4524 |
| 0.0479 | 47.0 | 282 | 4.3503 | 0.4524 |
| 0.0479 | 48.0 | 288 | 4.3503 | 0.4524 |
| 0.0488 | 49.0 | 294 | 4.3503 | 0.4524 |
| 0.0619 | 50.0 | 300 | 4.3503 | 0.4524 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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