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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_1x_beit_base_sgd_001_fold3
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: 0.3023255813953488
---
<!-- 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_1x_beit_base_sgd_001_fold3
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: 1.3325
- Accuracy: 0.3023
## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 6 | 1.5424 | 0.2558 |
| 1.5472 | 2.0 | 12 | 1.5114 | 0.2326 |
| 1.5472 | 3.0 | 18 | 1.4888 | 0.2791 |
| 1.4947 | 4.0 | 24 | 1.4715 | 0.2558 |
| 1.4055 | 5.0 | 30 | 1.4594 | 0.2791 |
| 1.4055 | 6.0 | 36 | 1.4478 | 0.3256 |
| 1.389 | 7.0 | 42 | 1.4378 | 0.3023 |
| 1.389 | 8.0 | 48 | 1.4298 | 0.3256 |
| 1.3593 | 9.0 | 54 | 1.4226 | 0.3488 |
| 1.3527 | 10.0 | 60 | 1.4160 | 0.3488 |
| 1.3527 | 11.0 | 66 | 1.4104 | 0.3488 |
| 1.3352 | 12.0 | 72 | 1.4055 | 0.3488 |
| 1.3352 | 13.0 | 78 | 1.4005 | 0.3721 |
| 1.2989 | 14.0 | 84 | 1.3949 | 0.3721 |
| 1.3078 | 15.0 | 90 | 1.3896 | 0.3721 |
| 1.3078 | 16.0 | 96 | 1.3853 | 0.3721 |
| 1.2945 | 17.0 | 102 | 1.3807 | 0.3488 |
| 1.2945 | 18.0 | 108 | 1.3772 | 0.3721 |
| 1.2862 | 19.0 | 114 | 1.3730 | 0.3488 |
| 1.2665 | 20.0 | 120 | 1.3692 | 0.3488 |
| 1.2665 | 21.0 | 126 | 1.3663 | 0.3488 |
| 1.2571 | 22.0 | 132 | 1.3633 | 0.3488 |
| 1.2571 | 23.0 | 138 | 1.3594 | 0.3488 |
| 1.2478 | 24.0 | 144 | 1.3564 | 0.3488 |
| 1.2356 | 25.0 | 150 | 1.3537 | 0.3488 |
| 1.2356 | 26.0 | 156 | 1.3506 | 0.3256 |
| 1.253 | 27.0 | 162 | 1.3489 | 0.3256 |
| 1.253 | 28.0 | 168 | 1.3460 | 0.3256 |
| 1.2445 | 29.0 | 174 | 1.3442 | 0.3256 |
| 1.208 | 30.0 | 180 | 1.3430 | 0.3023 |
| 1.208 | 31.0 | 186 | 1.3417 | 0.3256 |
| 1.204 | 32.0 | 192 | 1.3396 | 0.3023 |
| 1.204 | 33.0 | 198 | 1.3381 | 0.3023 |
| 1.1994 | 34.0 | 204 | 1.3371 | 0.3023 |
| 1.1991 | 35.0 | 210 | 1.3357 | 0.3023 |
| 1.1991 | 36.0 | 216 | 1.3349 | 0.3023 |
| 1.1819 | 37.0 | 222 | 1.3343 | 0.3023 |
| 1.1819 | 38.0 | 228 | 1.3338 | 0.3023 |
| 1.1973 | 39.0 | 234 | 1.3332 | 0.3023 |
| 1.1899 | 40.0 | 240 | 1.3328 | 0.3023 |
| 1.1899 | 41.0 | 246 | 1.3326 | 0.3023 |
| 1.1779 | 42.0 | 252 | 1.3325 | 0.3023 |
| 1.1779 | 43.0 | 258 | 1.3325 | 0.3023 |
| 1.1962 | 44.0 | 264 | 1.3325 | 0.3023 |
| 1.2031 | 45.0 | 270 | 1.3325 | 0.3023 |
| 1.2031 | 46.0 | 276 | 1.3325 | 0.3023 |
| 1.1985 | 47.0 | 282 | 1.3325 | 0.3023 |
| 1.1985 | 48.0 | 288 | 1.3325 | 0.3023 |
| 1.1942 | 49.0 | 294 | 1.3325 | 0.3023 |
| 1.1653 | 50.0 | 300 | 1.3325 | 0.3023 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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