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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_adamax_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: 0.8
---
<!-- 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_adamax_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: 0.9719
- Accuracy: 0.8
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4817 | 1.0 | 27 | 0.8446 | 0.6889 |
| 0.1236 | 2.0 | 54 | 0.5416 | 0.8 |
| 0.0728 | 3.0 | 81 | 1.1383 | 0.7333 |
| 0.0137 | 4.0 | 108 | 0.8130 | 0.7556 |
| 0.0121 | 5.0 | 135 | 1.0498 | 0.7778 |
| 0.0052 | 6.0 | 162 | 1.2025 | 0.7333 |
| 0.0025 | 7.0 | 189 | 1.8500 | 0.6889 |
| 0.0027 | 8.0 | 216 | 1.2581 | 0.7333 |
| 0.0011 | 9.0 | 243 | 1.0128 | 0.7111 |
| 0.0002 | 10.0 | 270 | 1.1087 | 0.7111 |
| 0.0015 | 11.0 | 297 | 1.5799 | 0.6889 |
| 0.0003 | 12.0 | 324 | 1.1596 | 0.7333 |
| 0.0003 | 13.0 | 351 | 0.7321 | 0.8222 |
| 0.0002 | 14.0 | 378 | 0.7110 | 0.8444 |
| 0.0001 | 15.0 | 405 | 0.9712 | 0.8 |
| 0.0001 | 16.0 | 432 | 0.9021 | 0.8 |
| 0.0003 | 17.0 | 459 | 1.0755 | 0.7778 |
| 0.0001 | 18.0 | 486 | 0.9553 | 0.8 |
| 0.0001 | 19.0 | 513 | 0.7418 | 0.8 |
| 0.0001 | 20.0 | 540 | 0.8008 | 0.8222 |
| 0.0001 | 21.0 | 567 | 0.8246 | 0.8222 |
| 0.0002 | 22.0 | 594 | 1.0106 | 0.8 |
| 0.0006 | 23.0 | 621 | 1.3939 | 0.7111 |
| 0.0001 | 24.0 | 648 | 1.1381 | 0.7111 |
| 0.0002 | 25.0 | 675 | 1.0384 | 0.7556 |
| 0.0001 | 26.0 | 702 | 0.9699 | 0.7556 |
| 0.0001 | 27.0 | 729 | 0.8959 | 0.7778 |
| 0.0 | 28.0 | 756 | 0.8640 | 0.8 |
| 0.0 | 29.0 | 783 | 0.8622 | 0.8 |
| 0.0001 | 30.0 | 810 | 1.0310 | 0.7778 |
| 0.0001 | 31.0 | 837 | 1.1256 | 0.7778 |
| 0.0001 | 32.0 | 864 | 1.0777 | 0.7778 |
| 0.0001 | 33.0 | 891 | 0.9925 | 0.7556 |
| 0.0001 | 34.0 | 918 | 0.9854 | 0.7778 |
| 0.0 | 35.0 | 945 | 0.9843 | 0.7778 |
| 0.0 | 36.0 | 972 | 0.9861 | 0.7778 |
| 0.0 | 37.0 | 999 | 1.0844 | 0.8222 |
| 0.0 | 38.0 | 1026 | 1.0708 | 0.8222 |
| 0.0001 | 39.0 | 1053 | 1.0786 | 0.8 |
| 0.0 | 40.0 | 1080 | 1.0854 | 0.8 |
| 0.001 | 41.0 | 1107 | 1.0589 | 0.8 |
| 0.0001 | 42.0 | 1134 | 1.1362 | 0.7556 |
| 0.0028 | 43.0 | 1161 | 1.0635 | 0.8 |
| 0.0 | 44.0 | 1188 | 0.9767 | 0.8 |
| 0.0 | 45.0 | 1215 | 0.9696 | 0.8 |
| 0.0003 | 46.0 | 1242 | 0.9742 | 0.8 |
| 0.0 | 47.0 | 1269 | 0.9715 | 0.8 |
| 0.0 | 48.0 | 1296 | 0.9720 | 0.8 |
| 0.0001 | 49.0 | 1323 | 0.9719 | 0.8 |
| 0.0001 | 50.0 | 1350 | 0.9719 | 0.8 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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