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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_0001_fold5
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: 0.8292682926829268
---
<!-- 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_0001_fold5
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: 0.8158
- Accuracy: 0.8293
## 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: 0.0001
- 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 | 1.1847 | 0.3902 |
| 1.4269 | 2.0 | 12 | 0.7266 | 0.7073 |
| 1.4269 | 3.0 | 18 | 0.6792 | 0.7073 |
| 0.5553 | 4.0 | 24 | 0.4456 | 0.7805 |
| 0.1357 | 5.0 | 30 | 0.2904 | 0.9024 |
| 0.1357 | 6.0 | 36 | 0.6815 | 0.8049 |
| 0.0115 | 7.0 | 42 | 0.6208 | 0.8049 |
| 0.0115 | 8.0 | 48 | 0.5124 | 0.8537 |
| 0.0146 | 9.0 | 54 | 0.7063 | 0.7805 |
| 0.0021 | 10.0 | 60 | 0.7320 | 0.8049 |
| 0.0021 | 11.0 | 66 | 0.5435 | 0.8537 |
| 0.0012 | 12.0 | 72 | 0.6105 | 0.8293 |
| 0.0012 | 13.0 | 78 | 0.6174 | 0.8537 |
| 0.0009 | 14.0 | 84 | 0.6224 | 0.8293 |
| 0.0011 | 15.0 | 90 | 0.5560 | 0.8293 |
| 0.0011 | 16.0 | 96 | 0.6136 | 0.8293 |
| 0.0005 | 17.0 | 102 | 0.6179 | 0.8537 |
| 0.0005 | 18.0 | 108 | 0.6489 | 0.8049 |
| 0.0019 | 19.0 | 114 | 0.7624 | 0.7561 |
| 0.0003 | 20.0 | 120 | 0.8499 | 0.7561 |
| 0.0003 | 21.0 | 126 | 0.8910 | 0.7805 |
| 0.0005 | 22.0 | 132 | 0.7310 | 0.7805 |
| 0.0005 | 23.0 | 138 | 0.6709 | 0.8049 |
| 0.0003 | 24.0 | 144 | 0.6558 | 0.8049 |
| 0.0004 | 25.0 | 150 | 0.6700 | 0.8049 |
| 0.0004 | 26.0 | 156 | 0.6879 | 0.8049 |
| 0.0003 | 27.0 | 162 | 0.7678 | 0.8049 |
| 0.0003 | 28.0 | 168 | 0.8154 | 0.8049 |
| 0.0002 | 29.0 | 174 | 0.8459 | 0.8049 |
| 0.0002 | 30.0 | 180 | 0.8632 | 0.8049 |
| 0.0002 | 31.0 | 186 | 0.8601 | 0.8049 |
| 0.001 | 32.0 | 192 | 0.8142 | 0.8049 |
| 0.001 | 33.0 | 198 | 0.7931 | 0.8049 |
| 0.0005 | 34.0 | 204 | 0.7822 | 0.8049 |
| 0.0004 | 35.0 | 210 | 0.7974 | 0.8293 |
| 0.0004 | 36.0 | 216 | 0.8092 | 0.8293 |
| 0.0001 | 37.0 | 222 | 0.8155 | 0.8293 |
| 0.0001 | 38.0 | 228 | 0.8178 | 0.8293 |
| 0.0001 | 39.0 | 234 | 0.8178 | 0.8293 |
| 0.0002 | 40.0 | 240 | 0.8165 | 0.8293 |
| 0.0002 | 41.0 | 246 | 0.8159 | 0.8293 |
| 0.0004 | 42.0 | 252 | 0.8158 | 0.8293 |
| 0.0004 | 43.0 | 258 | 0.8158 | 0.8293 |
| 0.0003 | 44.0 | 264 | 0.8158 | 0.8293 |
| 0.0001 | 45.0 | 270 | 0.8158 | 0.8293 |
| 0.0001 | 46.0 | 276 | 0.8158 | 0.8293 |
| 0.0011 | 47.0 | 282 | 0.8158 | 0.8293 |
| 0.0011 | 48.0 | 288 | 0.8158 | 0.8293 |
| 0.0001 | 49.0 | 294 | 0.8158 | 0.8293 |
| 0.0001 | 50.0 | 300 | 0.8158 | 0.8293 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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