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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_fold2
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: 0.5111111111111111
---
<!-- 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_fold2
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: 1.1467
- Accuracy: 0.5111
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4631 | 1.0 | 27 | 1.4879 | 0.2667 |
| 1.4591 | 2.0 | 54 | 1.4319 | 0.2667 |
| 1.4073 | 3.0 | 81 | 1.3901 | 0.2667 |
| 1.3795 | 4.0 | 108 | 1.3753 | 0.2667 |
| 1.2841 | 5.0 | 135 | 1.3518 | 0.2889 |
| 1.2567 | 6.0 | 162 | 1.3273 | 0.3333 |
| 1.2476 | 7.0 | 189 | 1.3161 | 0.3333 |
| 1.2159 | 8.0 | 216 | 1.3027 | 0.3333 |
| 1.1714 | 9.0 | 243 | 1.2935 | 0.3556 |
| 1.1327 | 10.0 | 270 | 1.2804 | 0.4 |
| 1.1283 | 11.0 | 297 | 1.2705 | 0.4 |
| 1.1211 | 12.0 | 324 | 1.2662 | 0.4 |
| 1.085 | 13.0 | 351 | 1.2507 | 0.4 |
| 1.0792 | 14.0 | 378 | 1.2454 | 0.4222 |
| 1.0431 | 15.0 | 405 | 1.2358 | 0.4222 |
| 1.0262 | 16.0 | 432 | 1.2333 | 0.4 |
| 1.0339 | 17.0 | 459 | 1.2202 | 0.4 |
| 1.054 | 18.0 | 486 | 1.2246 | 0.4 |
| 0.9922 | 19.0 | 513 | 1.2085 | 0.4444 |
| 0.9927 | 20.0 | 540 | 1.1996 | 0.4667 |
| 0.9784 | 21.0 | 567 | 1.1934 | 0.4889 |
| 0.9509 | 22.0 | 594 | 1.2003 | 0.4889 |
| 0.8926 | 23.0 | 621 | 1.1949 | 0.4667 |
| 0.9112 | 24.0 | 648 | 1.1944 | 0.4667 |
| 0.9183 | 25.0 | 675 | 1.1878 | 0.4667 |
| 0.922 | 26.0 | 702 | 1.1803 | 0.4889 |
| 0.9154 | 27.0 | 729 | 1.1775 | 0.5111 |
| 0.8756 | 28.0 | 756 | 1.1755 | 0.5111 |
| 0.8844 | 29.0 | 783 | 1.1704 | 0.5111 |
| 0.9306 | 30.0 | 810 | 1.1638 | 0.4889 |
| 0.8332 | 31.0 | 837 | 1.1571 | 0.4889 |
| 0.8854 | 32.0 | 864 | 1.1562 | 0.4889 |
| 0.869 | 33.0 | 891 | 1.1538 | 0.4889 |
| 0.8165 | 34.0 | 918 | 1.1565 | 0.4889 |
| 0.8544 | 35.0 | 945 | 1.1478 | 0.4889 |
| 0.7949 | 36.0 | 972 | 1.1509 | 0.4889 |
| 0.7913 | 37.0 | 999 | 1.1517 | 0.4889 |
| 0.8304 | 38.0 | 1026 | 1.1504 | 0.4889 |
| 0.8034 | 39.0 | 1053 | 1.1530 | 0.5111 |
| 0.7958 | 40.0 | 1080 | 1.1506 | 0.4889 |
| 0.7773 | 41.0 | 1107 | 1.1491 | 0.5111 |
| 0.7795 | 42.0 | 1134 | 1.1490 | 0.5111 |
| 0.8191 | 43.0 | 1161 | 1.1489 | 0.5111 |
| 0.7893 | 44.0 | 1188 | 1.1487 | 0.5111 |
| 0.8109 | 45.0 | 1215 | 1.1476 | 0.5111 |
| 0.7952 | 46.0 | 1242 | 1.1473 | 0.5111 |
| 0.798 | 47.0 | 1269 | 1.1472 | 0.5111 |
| 0.8109 | 48.0 | 1296 | 1.1467 | 0.5111 |
| 0.8173 | 49.0 | 1323 | 1.1467 | 0.5111 |
| 0.7998 | 50.0 | 1350 | 1.1467 | 0.5111 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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