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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_5x_beit_base_sgd_001_fold1
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: 0.4
---
<!-- 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_5x_beit_base_sgd_001_fold1
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: 1.5176
- Accuracy: 0.4
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4454 | 1.0 | 27 | 1.5496 | 0.2667 |
| 1.3864 | 2.0 | 54 | 1.5125 | 0.2667 |
| 1.3701 | 3.0 | 81 | 1.4961 | 0.2667 |
| 1.3167 | 4.0 | 108 | 1.5066 | 0.2889 |
| 1.2134 | 5.0 | 135 | 1.5082 | 0.3333 |
| 1.1476 | 6.0 | 162 | 1.5110 | 0.3333 |
| 1.1471 | 7.0 | 189 | 1.5248 | 0.3333 |
| 1.1363 | 8.0 | 216 | 1.5434 | 0.3556 |
| 1.0955 | 9.0 | 243 | 1.5579 | 0.3778 |
| 1.0745 | 10.0 | 270 | 1.5619 | 0.3333 |
| 1.0401 | 11.0 | 297 | 1.5614 | 0.3333 |
| 1.0047 | 12.0 | 324 | 1.5711 | 0.3333 |
| 1.0055 | 13.0 | 351 | 1.5627 | 0.3333 |
| 0.9832 | 14.0 | 378 | 1.5529 | 0.3333 |
| 0.9676 | 15.0 | 405 | 1.5726 | 0.3333 |
| 0.9641 | 16.0 | 432 | 1.5677 | 0.3333 |
| 0.9328 | 17.0 | 459 | 1.5601 | 0.3333 |
| 0.9518 | 18.0 | 486 | 1.5678 | 0.3333 |
| 0.9109 | 19.0 | 513 | 1.5762 | 0.3333 |
| 0.9218 | 20.0 | 540 | 1.5662 | 0.3333 |
| 0.8731 | 21.0 | 567 | 1.5698 | 0.3333 |
| 0.8636 | 22.0 | 594 | 1.5667 | 0.3333 |
| 0.8235 | 23.0 | 621 | 1.5658 | 0.3333 |
| 0.8569 | 24.0 | 648 | 1.5702 | 0.3333 |
| 0.8347 | 25.0 | 675 | 1.5568 | 0.3333 |
| 0.8597 | 26.0 | 702 | 1.5638 | 0.3333 |
| 0.8371 | 27.0 | 729 | 1.5541 | 0.3333 |
| 0.8073 | 28.0 | 756 | 1.5468 | 0.3556 |
| 0.8391 | 29.0 | 783 | 1.5399 | 0.3556 |
| 0.8305 | 30.0 | 810 | 1.5379 | 0.3556 |
| 0.7771 | 31.0 | 837 | 1.5433 | 0.3778 |
| 0.8158 | 32.0 | 864 | 1.5408 | 0.3556 |
| 0.8402 | 33.0 | 891 | 1.5426 | 0.3778 |
| 0.7881 | 34.0 | 918 | 1.5356 | 0.3778 |
| 0.798 | 35.0 | 945 | 1.5324 | 0.4 |
| 0.75 | 36.0 | 972 | 1.5330 | 0.4 |
| 0.7699 | 37.0 | 999 | 1.5355 | 0.3778 |
| 0.7585 | 38.0 | 1026 | 1.5345 | 0.4 |
| 0.7272 | 39.0 | 1053 | 1.5315 | 0.4 |
| 0.7453 | 40.0 | 1080 | 1.5287 | 0.4 |
| 0.7465 | 41.0 | 1107 | 1.5241 | 0.4 |
| 0.7238 | 42.0 | 1134 | 1.5231 | 0.4 |
| 0.7663 | 43.0 | 1161 | 1.5207 | 0.4 |
| 0.7014 | 44.0 | 1188 | 1.5176 | 0.4 |
| 0.7481 | 45.0 | 1215 | 1.5184 | 0.4 |
| 0.7298 | 46.0 | 1242 | 1.5191 | 0.4 |
| 0.7342 | 47.0 | 1269 | 1.5176 | 0.4 |
| 0.706 | 48.0 | 1296 | 1.5175 | 0.4 |
| 0.7649 | 49.0 | 1323 | 1.5176 | 0.4 |
| 0.7295 | 50.0 | 1350 | 1.5176 | 0.4 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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