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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_00001_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: 0.813953488372093
---
<!-- 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_00001_fold3
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: 0.5847
- Accuracy: 0.8140
## 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: 1e-05
- 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 | 1.3689 | 0.2558 |
| 1.2857 | 2.0 | 12 | 1.2466 | 0.4651 |
| 1.2857 | 3.0 | 18 | 1.1312 | 0.5116 |
| 0.9708 | 4.0 | 24 | 1.0630 | 0.5581 |
| 0.7059 | 5.0 | 30 | 0.9958 | 0.6279 |
| 0.7059 | 6.0 | 36 | 0.9376 | 0.6977 |
| 0.5317 | 7.0 | 42 | 0.9138 | 0.6977 |
| 0.5317 | 8.0 | 48 | 0.8910 | 0.7209 |
| 0.4018 | 9.0 | 54 | 0.8263 | 0.7209 |
| 0.2986 | 10.0 | 60 | 0.8004 | 0.7442 |
| 0.2986 | 11.0 | 66 | 0.7624 | 0.7442 |
| 0.246 | 12.0 | 72 | 0.7431 | 0.7442 |
| 0.246 | 13.0 | 78 | 0.7355 | 0.7674 |
| 0.2027 | 14.0 | 84 | 0.7048 | 0.7674 |
| 0.1517 | 15.0 | 90 | 0.6855 | 0.7674 |
| 0.1517 | 16.0 | 96 | 0.6737 | 0.7907 |
| 0.1364 | 17.0 | 102 | 0.6501 | 0.7907 |
| 0.1364 | 18.0 | 108 | 0.6600 | 0.7674 |
| 0.1145 | 19.0 | 114 | 0.6690 | 0.7674 |
| 0.1069 | 20.0 | 120 | 0.6546 | 0.7674 |
| 0.1069 | 21.0 | 126 | 0.6296 | 0.7674 |
| 0.0848 | 22.0 | 132 | 0.6148 | 0.7907 |
| 0.0848 | 23.0 | 138 | 0.6215 | 0.7907 |
| 0.0728 | 24.0 | 144 | 0.6245 | 0.7907 |
| 0.0711 | 25.0 | 150 | 0.6128 | 0.7907 |
| 0.0711 | 26.0 | 156 | 0.6151 | 0.7907 |
| 0.0595 | 27.0 | 162 | 0.6249 | 0.7907 |
| 0.0595 | 28.0 | 168 | 0.6313 | 0.7907 |
| 0.0729 | 29.0 | 174 | 0.6189 | 0.7907 |
| 0.0453 | 30.0 | 180 | 0.6035 | 0.7907 |
| 0.0453 | 31.0 | 186 | 0.5936 | 0.8140 |
| 0.0572 | 32.0 | 192 | 0.5852 | 0.8140 |
| 0.0572 | 33.0 | 198 | 0.5840 | 0.8140 |
| 0.0512 | 34.0 | 204 | 0.5836 | 0.8140 |
| 0.0479 | 35.0 | 210 | 0.5806 | 0.8140 |
| 0.0479 | 36.0 | 216 | 0.5792 | 0.8140 |
| 0.0352 | 37.0 | 222 | 0.5787 | 0.8140 |
| 0.0352 | 38.0 | 228 | 0.5803 | 0.8140 |
| 0.0412 | 39.0 | 234 | 0.5826 | 0.8140 |
| 0.0379 | 40.0 | 240 | 0.5843 | 0.8140 |
| 0.0379 | 41.0 | 246 | 0.5847 | 0.8140 |
| 0.0381 | 42.0 | 252 | 0.5847 | 0.8140 |
| 0.0381 | 43.0 | 258 | 0.5847 | 0.8140 |
| 0.0582 | 44.0 | 264 | 0.5847 | 0.8140 |
| 0.0396 | 45.0 | 270 | 0.5847 | 0.8140 |
| 0.0396 | 46.0 | 276 | 0.5847 | 0.8140 |
| 0.0561 | 47.0 | 282 | 0.5847 | 0.8140 |
| 0.0561 | 48.0 | 288 | 0.5847 | 0.8140 |
| 0.047 | 49.0 | 294 | 0.5847 | 0.8140 |
| 0.0342 | 50.0 | 300 | 0.5847 | 0.8140 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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