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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_00001_fold5
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: 0.24390243902439024
---
<!-- 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_00001_fold5
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: 1.6137
- Accuracy: 0.2439
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5748 | 1.0 | 28 | 1.6349 | 0.2439 |
| 1.5498 | 2.0 | 56 | 1.6339 | 0.2439 |
| 1.5458 | 3.0 | 84 | 1.6329 | 0.2439 |
| 1.5997 | 4.0 | 112 | 1.6319 | 0.2439 |
| 1.5518 | 5.0 | 140 | 1.6310 | 0.2439 |
| 1.6078 | 6.0 | 168 | 1.6301 | 0.2439 |
| 1.6054 | 7.0 | 196 | 1.6292 | 0.2439 |
| 1.5635 | 8.0 | 224 | 1.6284 | 0.2439 |
| 1.5412 | 9.0 | 252 | 1.6276 | 0.2439 |
| 1.5684 | 10.0 | 280 | 1.6268 | 0.2439 |
| 1.5211 | 11.0 | 308 | 1.6261 | 0.2439 |
| 1.5857 | 12.0 | 336 | 1.6254 | 0.2439 |
| 1.5804 | 13.0 | 364 | 1.6248 | 0.2439 |
| 1.5778 | 14.0 | 392 | 1.6241 | 0.2439 |
| 1.5905 | 15.0 | 420 | 1.6235 | 0.2439 |
| 1.5552 | 16.0 | 448 | 1.6228 | 0.2439 |
| 1.5712 | 17.0 | 476 | 1.6222 | 0.2439 |
| 1.5113 | 18.0 | 504 | 1.6216 | 0.2439 |
| 1.5441 | 19.0 | 532 | 1.6210 | 0.2439 |
| 1.547 | 20.0 | 560 | 1.6205 | 0.2439 |
| 1.5712 | 21.0 | 588 | 1.6200 | 0.2439 |
| 1.595 | 22.0 | 616 | 1.6195 | 0.2439 |
| 1.6001 | 23.0 | 644 | 1.6190 | 0.2439 |
| 1.6008 | 24.0 | 672 | 1.6185 | 0.2439 |
| 1.5469 | 25.0 | 700 | 1.6181 | 0.2439 |
| 1.567 | 26.0 | 728 | 1.6177 | 0.2439 |
| 1.618 | 27.0 | 756 | 1.6173 | 0.2439 |
| 1.4849 | 28.0 | 784 | 1.6170 | 0.2439 |
| 1.5706 | 29.0 | 812 | 1.6166 | 0.2439 |
| 1.5269 | 30.0 | 840 | 1.6163 | 0.2439 |
| 1.588 | 31.0 | 868 | 1.6160 | 0.2439 |
| 1.5207 | 32.0 | 896 | 1.6157 | 0.2439 |
| 1.5395 | 33.0 | 924 | 1.6155 | 0.2439 |
| 1.5482 | 34.0 | 952 | 1.6152 | 0.2439 |
| 1.6004 | 35.0 | 980 | 1.6150 | 0.2439 |
| 1.5389 | 36.0 | 1008 | 1.6148 | 0.2439 |
| 1.5566 | 37.0 | 1036 | 1.6146 | 0.2439 |
| 1.54 | 38.0 | 1064 | 1.6145 | 0.2439 |
| 1.5715 | 39.0 | 1092 | 1.6143 | 0.2439 |
| 1.5148 | 40.0 | 1120 | 1.6142 | 0.2439 |
| 1.5688 | 41.0 | 1148 | 1.6141 | 0.2439 |
| 1.5803 | 42.0 | 1176 | 1.6140 | 0.2439 |
| 1.5477 | 43.0 | 1204 | 1.6139 | 0.2439 |
| 1.5623 | 44.0 | 1232 | 1.6138 | 0.2439 |
| 1.5648 | 45.0 | 1260 | 1.6137 | 0.2439 |
| 1.5331 | 46.0 | 1288 | 1.6137 | 0.2439 |
| 1.5791 | 47.0 | 1316 | 1.6137 | 0.2439 |
| 1.5282 | 48.0 | 1344 | 1.6137 | 0.2439 |
| 1.5715 | 49.0 | 1372 | 1.6137 | 0.2439 |
| 1.5955 | 50.0 | 1400 | 1.6137 | 0.2439 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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