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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_fold4
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: 0.9285714285714286
---
<!-- 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_fold4
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: 0.2768
- Accuracy: 0.9286
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2143 | 1.0 | 28 | 1.1034 | 0.5714 |
| 0.7775 | 2.0 | 56 | 0.7868 | 0.7143 |
| 0.4533 | 3.0 | 84 | 0.5700 | 0.8571 |
| 0.3037 | 4.0 | 112 | 0.4325 | 0.9048 |
| 0.1612 | 5.0 | 140 | 0.3176 | 0.9524 |
| 0.1058 | 6.0 | 168 | 0.2780 | 0.9524 |
| 0.0913 | 7.0 | 196 | 0.2215 | 0.9524 |
| 0.0514 | 8.0 | 224 | 0.1972 | 0.9524 |
| 0.0348 | 9.0 | 252 | 0.1996 | 0.9524 |
| 0.0351 | 10.0 | 280 | 0.1992 | 0.9524 |
| 0.0183 | 11.0 | 308 | 0.2116 | 0.9286 |
| 0.0237 | 12.0 | 336 | 0.2277 | 0.9286 |
| 0.0106 | 13.0 | 364 | 0.2270 | 0.9286 |
| 0.0108 | 14.0 | 392 | 0.2101 | 0.9524 |
| 0.0149 | 15.0 | 420 | 0.2231 | 0.9524 |
| 0.0076 | 16.0 | 448 | 0.2350 | 0.9048 |
| 0.0086 | 17.0 | 476 | 0.2204 | 0.9286 |
| 0.0033 | 18.0 | 504 | 0.2707 | 0.9286 |
| 0.0048 | 19.0 | 532 | 0.2227 | 0.9286 |
| 0.0041 | 20.0 | 560 | 0.2590 | 0.9286 |
| 0.0023 | 21.0 | 588 | 0.2904 | 0.9048 |
| 0.0045 | 22.0 | 616 | 0.2887 | 0.9286 |
| 0.0027 | 23.0 | 644 | 0.2955 | 0.9286 |
| 0.0033 | 24.0 | 672 | 0.2912 | 0.9286 |
| 0.0028 | 25.0 | 700 | 0.2636 | 0.9286 |
| 0.0018 | 26.0 | 728 | 0.2618 | 0.9286 |
| 0.0028 | 27.0 | 756 | 0.2893 | 0.9286 |
| 0.0019 | 28.0 | 784 | 0.2937 | 0.9286 |
| 0.0014 | 29.0 | 812 | 0.2912 | 0.9048 |
| 0.0031 | 30.0 | 840 | 0.2819 | 0.9048 |
| 0.0013 | 31.0 | 868 | 0.2819 | 0.9524 |
| 0.006 | 32.0 | 896 | 0.2996 | 0.9286 |
| 0.001 | 33.0 | 924 | 0.2836 | 0.9048 |
| 0.0011 | 34.0 | 952 | 0.2841 | 0.9286 |
| 0.0015 | 35.0 | 980 | 0.2638 | 0.9286 |
| 0.0022 | 36.0 | 1008 | 0.2845 | 0.9286 |
| 0.001 | 37.0 | 1036 | 0.2920 | 0.9286 |
| 0.0015 | 38.0 | 1064 | 0.2827 | 0.9286 |
| 0.0029 | 39.0 | 1092 | 0.2797 | 0.9286 |
| 0.002 | 40.0 | 1120 | 0.2954 | 0.9286 |
| 0.0017 | 41.0 | 1148 | 0.3039 | 0.9286 |
| 0.001 | 42.0 | 1176 | 0.3143 | 0.9286 |
| 0.0014 | 43.0 | 1204 | 0.3005 | 0.9286 |
| 0.0014 | 44.0 | 1232 | 0.2937 | 0.9286 |
| 0.0019 | 45.0 | 1260 | 0.2833 | 0.9286 |
| 0.0042 | 46.0 | 1288 | 0.2805 | 0.9286 |
| 0.0013 | 47.0 | 1316 | 0.2768 | 0.9286 |
| 0.0008 | 48.0 | 1344 | 0.2768 | 0.9286 |
| 0.0031 | 49.0 | 1372 | 0.2768 | 0.9286 |
| 0.0013 | 50.0 | 1400 | 0.2768 | 0.9286 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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