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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_00001_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: 0.6888888888888889
---
<!-- 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_00001_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: 1.3063
- Accuracy: 0.6889
## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2914 | 1.0 | 27 | 1.3981 | 0.3111 |
| 0.7752 | 2.0 | 54 | 1.2587 | 0.4222 |
| 0.473 | 3.0 | 81 | 1.1213 | 0.6 |
| 0.3517 | 4.0 | 108 | 1.0654 | 0.5778 |
| 0.2036 | 5.0 | 135 | 0.9700 | 0.6222 |
| 0.1396 | 6.0 | 162 | 0.9127 | 0.6444 |
| 0.1055 | 7.0 | 189 | 1.0554 | 0.6222 |
| 0.0683 | 8.0 | 216 | 0.9132 | 0.6222 |
| 0.0509 | 9.0 | 243 | 1.0907 | 0.6222 |
| 0.0285 | 10.0 | 270 | 1.0220 | 0.6667 |
| 0.0302 | 11.0 | 297 | 0.9814 | 0.6667 |
| 0.0178 | 12.0 | 324 | 1.0288 | 0.6667 |
| 0.0215 | 13.0 | 351 | 0.9906 | 0.6667 |
| 0.0098 | 14.0 | 378 | 0.9906 | 0.6667 |
| 0.0094 | 15.0 | 405 | 0.9909 | 0.6667 |
| 0.0079 | 16.0 | 432 | 1.0583 | 0.6889 |
| 0.0176 | 17.0 | 459 | 1.0002 | 0.7111 |
| 0.0071 | 18.0 | 486 | 1.1076 | 0.7111 |
| 0.0077 | 19.0 | 513 | 1.2658 | 0.7111 |
| 0.0085 | 20.0 | 540 | 1.2202 | 0.7111 |
| 0.0042 | 21.0 | 567 | 1.1485 | 0.6889 |
| 0.0109 | 22.0 | 594 | 1.1833 | 0.6667 |
| 0.0017 | 23.0 | 621 | 1.2496 | 0.6667 |
| 0.0025 | 24.0 | 648 | 1.2268 | 0.6667 |
| 0.0049 | 25.0 | 675 | 1.1304 | 0.6889 |
| 0.0023 | 26.0 | 702 | 1.0752 | 0.6667 |
| 0.002 | 27.0 | 729 | 1.3029 | 0.6889 |
| 0.0019 | 28.0 | 756 | 1.1867 | 0.6444 |
| 0.0014 | 29.0 | 783 | 1.1802 | 0.7333 |
| 0.002 | 30.0 | 810 | 1.3660 | 0.7111 |
| 0.0126 | 31.0 | 837 | 1.3022 | 0.6889 |
| 0.002 | 32.0 | 864 | 1.3902 | 0.6667 |
| 0.0046 | 33.0 | 891 | 1.3937 | 0.6889 |
| 0.0019 | 34.0 | 918 | 1.3856 | 0.7333 |
| 0.0048 | 35.0 | 945 | 1.3752 | 0.6667 |
| 0.002 | 36.0 | 972 | 1.3963 | 0.6667 |
| 0.0009 | 37.0 | 999 | 1.3895 | 0.7111 |
| 0.001 | 38.0 | 1026 | 1.2536 | 0.6889 |
| 0.0016 | 39.0 | 1053 | 1.2991 | 0.6667 |
| 0.0008 | 40.0 | 1080 | 1.2492 | 0.6889 |
| 0.0031 | 41.0 | 1107 | 1.2808 | 0.6889 |
| 0.0025 | 42.0 | 1134 | 1.3015 | 0.6667 |
| 0.0032 | 43.0 | 1161 | 1.3785 | 0.7111 |
| 0.0006 | 44.0 | 1188 | 1.3466 | 0.6889 |
| 0.004 | 45.0 | 1215 | 1.3569 | 0.6667 |
| 0.0022 | 46.0 | 1242 | 1.3406 | 0.6444 |
| 0.0027 | 47.0 | 1269 | 1.3081 | 0.6889 |
| 0.0015 | 48.0 | 1296 | 1.3063 | 0.6889 |
| 0.002 | 49.0 | 1323 | 1.3063 | 0.6889 |
| 0.003 | 50.0 | 1350 | 1.3063 | 0.6889 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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