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_fold2
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: 0.26666666666666666
hushem_1x_beit_base_sgd_0001_fold2
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: 1.4763
- Accuracy: 0.2667
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 | 1.5508 | 0.2667 |
| 1.5993 | 2.0 | 12 | 1.5460 | 0.2667 |
| 1.5993 | 3.0 | 18 | 1.5415 | 0.2667 |
| 1.5379 | 4.0 | 24 | 1.5376 | 0.2667 |
| 1.5842 | 5.0 | 30 | 1.5337 | 0.2667 |
| 1.5842 | 6.0 | 36 | 1.5302 | 0.2667 |
| 1.5559 | 7.0 | 42 | 1.5267 | 0.2667 |
| 1.5559 | 8.0 | 48 | 1.5233 | 0.2667 |
| 1.5583 | 9.0 | 54 | 1.5200 | 0.2667 |
| 1.5216 | 10.0 | 60 | 1.5170 | 0.2667 |
| 1.5216 | 11.0 | 66 | 1.5141 | 0.2667 |
| 1.5475 | 12.0 | 72 | 1.5116 | 0.2667 |
| 1.5475 | 13.0 | 78 | 1.5088 | 0.2667 |
| 1.5228 | 14.0 | 84 | 1.5063 | 0.2667 |
| 1.5337 | 15.0 | 90 | 1.5038 | 0.2667 |
| 1.5337 | 16.0 | 96 | 1.5015 | 0.2667 |
| 1.5424 | 17.0 | 102 | 1.4994 | 0.2667 |
| 1.5424 | 18.0 | 108 | 1.4973 | 0.2667 |
| 1.5261 | 19.0 | 114 | 1.4953 | 0.2667 |
| 1.5374 | 20.0 | 120 | 1.4936 | 0.2667 |
| 1.5374 | 21.0 | 126 | 1.4921 | 0.2667 |
| 1.5211 | 22.0 | 132 | 1.4905 | 0.2667 |
| 1.5211 | 23.0 | 138 | 1.4888 | 0.2667 |
| 1.5308 | 24.0 | 144 | 1.4875 | 0.2667 |
| 1.501 | 25.0 | 150 | 1.4863 | 0.2667 |
| 1.501 | 26.0 | 156 | 1.4851 | 0.2667 |
| 1.4969 | 27.0 | 162 | 1.4841 | 0.2667 |
| 1.4969 | 28.0 | 168 | 1.4832 | 0.2667 |
| 1.4796 | 29.0 | 174 | 1.4822 | 0.2667 |
| 1.5135 | 30.0 | 180 | 1.4813 | 0.2667 |
| 1.5135 | 31.0 | 186 | 1.4804 | 0.2667 |
| 1.4924 | 32.0 | 192 | 1.4797 | 0.2667 |
| 1.4924 | 33.0 | 198 | 1.4791 | 0.2667 |
| 1.4838 | 34.0 | 204 | 1.4785 | 0.2667 |
| 1.4833 | 35.0 | 210 | 1.4779 | 0.2667 |
| 1.4833 | 36.0 | 216 | 1.4775 | 0.2667 |
| 1.4826 | 37.0 | 222 | 1.4771 | 0.2667 |
| 1.4826 | 38.0 | 228 | 1.4768 | 0.2667 |
| 1.5058 | 39.0 | 234 | 1.4766 | 0.2667 |
| 1.4814 | 40.0 | 240 | 1.4764 | 0.2667 |
| 1.4814 | 41.0 | 246 | 1.4764 | 0.2667 |
| 1.4809 | 42.0 | 252 | 1.4763 | 0.2667 |
| 1.4809 | 43.0 | 258 | 1.4763 | 0.2667 |
| 1.5264 | 44.0 | 264 | 1.4763 | 0.2667 |
| 1.4935 | 45.0 | 270 | 1.4763 | 0.2667 |
| 1.4935 | 46.0 | 276 | 1.4763 | 0.2667 |
| 1.4909 | 47.0 | 282 | 1.4763 | 0.2667 |
| 1.4909 | 48.0 | 288 | 1.4763 | 0.2667 |
| 1.4851 | 49.0 | 294 | 1.4763 | 0.2667 |
| 1.5045 | 50.0 | 300 | 1.4763 | 0.2667 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0