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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_rms_0001_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: 0.35555555555555557
---
<!-- 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_rms_0001_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: 3.6811
- Accuracy: 0.3556
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4287 | 1.0 | 27 | 1.3926 | 0.2222 |
| 1.3907 | 2.0 | 54 | 1.3975 | 0.2667 |
| 1.358 | 3.0 | 81 | 1.5093 | 0.2444 |
| 1.3416 | 4.0 | 108 | 1.5118 | 0.2444 |
| 1.2056 | 5.0 | 135 | 1.4928 | 0.2444 |
| 1.1299 | 6.0 | 162 | 1.6562 | 0.2222 |
| 1.1641 | 7.0 | 189 | 1.5947 | 0.2444 |
| 1.1473 | 8.0 | 216 | 1.5964 | 0.2444 |
| 1.1298 | 9.0 | 243 | 1.7663 | 0.2444 |
| 1.1045 | 10.0 | 270 | 1.6309 | 0.3778 |
| 0.8985 | 11.0 | 297 | 1.6908 | 0.4 |
| 0.7744 | 12.0 | 324 | 1.3949 | 0.3556 |
| 0.7617 | 13.0 | 351 | 1.4646 | 0.3778 |
| 0.6843 | 14.0 | 378 | 1.5910 | 0.3778 |
| 0.6647 | 15.0 | 405 | 1.8050 | 0.4 |
| 0.6363 | 16.0 | 432 | 1.7016 | 0.3333 |
| 0.6362 | 17.0 | 459 | 1.8539 | 0.3778 |
| 0.6858 | 18.0 | 486 | 1.8678 | 0.3556 |
| 0.7039 | 19.0 | 513 | 1.5776 | 0.3556 |
| 0.6292 | 20.0 | 540 | 1.8552 | 0.3111 |
| 0.4567 | 21.0 | 567 | 1.7854 | 0.3556 |
| 0.5954 | 22.0 | 594 | 2.4822 | 0.3556 |
| 0.5737 | 23.0 | 621 | 2.0564 | 0.4 |
| 0.4941 | 24.0 | 648 | 1.9451 | 0.3111 |
| 0.523 | 25.0 | 675 | 2.0359 | 0.3778 |
| 0.5221 | 26.0 | 702 | 2.1184 | 0.4 |
| 0.4589 | 27.0 | 729 | 2.0471 | 0.3556 |
| 0.4473 | 28.0 | 756 | 2.5353 | 0.3556 |
| 0.4328 | 29.0 | 783 | 2.7479 | 0.3556 |
| 0.4259 | 30.0 | 810 | 2.2239 | 0.3778 |
| 0.3698 | 31.0 | 837 | 2.5363 | 0.3556 |
| 0.3577 | 32.0 | 864 | 2.5264 | 0.3556 |
| 0.3882 | 33.0 | 891 | 2.2649 | 0.3333 |
| 0.3526 | 34.0 | 918 | 2.6438 | 0.3556 |
| 0.2747 | 35.0 | 945 | 2.3584 | 0.3778 |
| 0.2842 | 36.0 | 972 | 2.8515 | 0.3556 |
| 0.2603 | 37.0 | 999 | 2.3416 | 0.3778 |
| 0.2268 | 38.0 | 1026 | 2.7485 | 0.3778 |
| 0.2 | 39.0 | 1053 | 3.3636 | 0.3333 |
| 0.2049 | 40.0 | 1080 | 3.1692 | 0.3333 |
| 0.1369 | 41.0 | 1107 | 3.3885 | 0.3556 |
| 0.1813 | 42.0 | 1134 | 3.3020 | 0.3333 |
| 0.1518 | 43.0 | 1161 | 2.8618 | 0.4 |
| 0.0986 | 44.0 | 1188 | 3.2902 | 0.3778 |
| 0.131 | 45.0 | 1215 | 3.3898 | 0.3333 |
| 0.0809 | 46.0 | 1242 | 3.5629 | 0.3333 |
| 0.048 | 47.0 | 1269 | 3.7516 | 0.3333 |
| 0.038 | 48.0 | 1296 | 3.6814 | 0.3556 |
| 0.0465 | 49.0 | 1323 | 3.6811 | 0.3556 |
| 0.0644 | 50.0 | 1350 | 3.6811 | 0.3556 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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