metadata
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_0001_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: 0.23255813953488372
hushem_1x_beit_base_sgd_0001_fold3
This model is a fine-tuned version of microsoft/beit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.5102
- Accuracy: 0.2326
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.5815 | 0.2558 |
| 1.5795 | 2.0 | 12 | 1.5768 | 0.2558 |
| 1.5795 | 3.0 | 18 | 1.5725 | 0.2558 |
| 1.5843 | 4.0 | 24 | 1.5685 | 0.2558 |
| 1.5064 | 5.0 | 30 | 1.5650 | 0.2558 |
| 1.5064 | 6.0 | 36 | 1.5613 | 0.2558 |
| 1.5264 | 7.0 | 42 | 1.5577 | 0.2558 |
| 1.5264 | 8.0 | 48 | 1.5544 | 0.2558 |
| 1.5341 | 9.0 | 54 | 1.5511 | 0.2558 |
| 1.5468 | 10.0 | 60 | 1.5482 | 0.2558 |
| 1.5468 | 11.0 | 66 | 1.5458 | 0.2558 |
| 1.5265 | 12.0 | 72 | 1.5432 | 0.2558 |
| 1.5265 | 13.0 | 78 | 1.5409 | 0.2558 |
| 1.4949 | 14.0 | 84 | 1.5386 | 0.2558 |
| 1.5252 | 15.0 | 90 | 1.5362 | 0.2558 |
| 1.5252 | 16.0 | 96 | 1.5341 | 0.2558 |
| 1.5295 | 17.0 | 102 | 1.5321 | 0.2558 |
| 1.5295 | 18.0 | 108 | 1.5302 | 0.2558 |
| 1.4916 | 19.0 | 114 | 1.5284 | 0.2558 |
| 1.4984 | 20.0 | 120 | 1.5267 | 0.2326 |
| 1.4984 | 21.0 | 126 | 1.5250 | 0.2326 |
| 1.5211 | 22.0 | 132 | 1.5235 | 0.2326 |
| 1.5211 | 23.0 | 138 | 1.5222 | 0.2326 |
| 1.506 | 24.0 | 144 | 1.5209 | 0.2326 |
| 1.483 | 25.0 | 150 | 1.5197 | 0.2326 |
| 1.483 | 26.0 | 156 | 1.5185 | 0.2326 |
| 1.5184 | 27.0 | 162 | 1.5173 | 0.2326 |
| 1.5184 | 28.0 | 168 | 1.5163 | 0.2326 |
| 1.536 | 29.0 | 174 | 1.5154 | 0.2326 |
| 1.4949 | 30.0 | 180 | 1.5146 | 0.2326 |
| 1.4949 | 31.0 | 186 | 1.5138 | 0.2326 |
| 1.5188 | 32.0 | 192 | 1.5132 | 0.2326 |
| 1.5188 | 33.0 | 198 | 1.5126 | 0.2326 |
| 1.4387 | 34.0 | 204 | 1.5120 | 0.2326 |
| 1.4953 | 35.0 | 210 | 1.5116 | 0.2326 |
| 1.4953 | 36.0 | 216 | 1.5112 | 0.2326 |
| 1.4703 | 37.0 | 222 | 1.5108 | 0.2326 |
| 1.4703 | 38.0 | 228 | 1.5106 | 0.2326 |
| 1.5017 | 39.0 | 234 | 1.5104 | 0.2326 |
| 1.4757 | 40.0 | 240 | 1.5103 | 0.2326 |
| 1.4757 | 41.0 | 246 | 1.5102 | 0.2326 |
| 1.4714 | 42.0 | 252 | 1.5102 | 0.2326 |
| 1.4714 | 43.0 | 258 | 1.5102 | 0.2326 |
| 1.4776 | 44.0 | 264 | 1.5102 | 0.2326 |
| 1.4921 | 45.0 | 270 | 1.5102 | 0.2326 |
| 1.4921 | 46.0 | 276 | 1.5102 | 0.2326 |
| 1.4896 | 47.0 | 282 | 1.5102 | 0.2326 |
| 1.4896 | 48.0 | 288 | 1.5102 | 0.2326 |
| 1.4789 | 49.0 | 294 | 1.5102 | 0.2326 |
| 1.4671 | 50.0 | 300 | 1.5102 | 0.2326 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0