metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_1x_deit_tiny_sgd_lr00001_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: 0.12195121951219512
hushem_1x_deit_tiny_sgd_lr00001_fold5
This model is a fine-tuned version of facebook/deit-tiny-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.6421
- Accuracy: 0.1220
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 |
|---|---|---|---|---|
| No log | 1.0 | 6 | 1.6490 | 0.1220 |
| 1.6062 | 2.0 | 12 | 1.6487 | 0.1220 |
| 1.6062 | 3.0 | 18 | 1.6483 | 0.1220 |
| 1.6229 | 4.0 | 24 | 1.6480 | 0.1220 |
| 1.5995 | 5.0 | 30 | 1.6477 | 0.1220 |
| 1.5995 | 6.0 | 36 | 1.6474 | 0.1220 |
| 1.5906 | 7.0 | 42 | 1.6470 | 0.1220 |
| 1.5906 | 8.0 | 48 | 1.6468 | 0.1220 |
| 1.609 | 9.0 | 54 | 1.6465 | 0.1220 |
| 1.6018 | 10.0 | 60 | 1.6462 | 0.1220 |
| 1.6018 | 11.0 | 66 | 1.6459 | 0.1220 |
| 1.5944 | 12.0 | 72 | 1.6457 | 0.1220 |
| 1.5944 | 13.0 | 78 | 1.6454 | 0.1220 |
| 1.6013 | 14.0 | 84 | 1.6452 | 0.1220 |
| 1.5987 | 15.0 | 90 | 1.6449 | 0.1220 |
| 1.5987 | 16.0 | 96 | 1.6447 | 0.1220 |
| 1.5899 | 17.0 | 102 | 1.6445 | 0.1220 |
| 1.5899 | 18.0 | 108 | 1.6443 | 0.1220 |
| 1.626 | 19.0 | 114 | 1.6441 | 0.1220 |
| 1.5972 | 20.0 | 120 | 1.6439 | 0.1220 |
| 1.5972 | 21.0 | 126 | 1.6437 | 0.1220 |
| 1.5649 | 22.0 | 132 | 1.6436 | 0.1220 |
| 1.5649 | 23.0 | 138 | 1.6434 | 0.1220 |
| 1.6699 | 24.0 | 144 | 1.6433 | 0.1220 |
| 1.5696 | 25.0 | 150 | 1.6431 | 0.1220 |
| 1.5696 | 26.0 | 156 | 1.6430 | 0.1220 |
| 1.5743 | 27.0 | 162 | 1.6429 | 0.1220 |
| 1.5743 | 28.0 | 168 | 1.6427 | 0.1220 |
| 1.6236 | 29.0 | 174 | 1.6426 | 0.1220 |
| 1.5936 | 30.0 | 180 | 1.6426 | 0.1220 |
| 1.5936 | 31.0 | 186 | 1.6425 | 0.1220 |
| 1.5875 | 32.0 | 192 | 1.6424 | 0.1220 |
| 1.5875 | 33.0 | 198 | 1.6423 | 0.1220 |
| 1.6171 | 34.0 | 204 | 1.6423 | 0.1220 |
| 1.5897 | 35.0 | 210 | 1.6422 | 0.1220 |
| 1.5897 | 36.0 | 216 | 1.6422 | 0.1220 |
| 1.5725 | 37.0 | 222 | 1.6421 | 0.1220 |
| 1.5725 | 38.0 | 228 | 1.6421 | 0.1220 |
| 1.6227 | 39.0 | 234 | 1.6421 | 0.1220 |
| 1.5924 | 40.0 | 240 | 1.6421 | 0.1220 |
| 1.5924 | 41.0 | 246 | 1.6421 | 0.1220 |
| 1.5811 | 42.0 | 252 | 1.6421 | 0.1220 |
| 1.5811 | 43.0 | 258 | 1.6421 | 0.1220 |
| 1.6072 | 44.0 | 264 | 1.6421 | 0.1220 |
| 1.5938 | 45.0 | 270 | 1.6421 | 0.1220 |
| 1.5938 | 46.0 | 276 | 1.6421 | 0.1220 |
| 1.6243 | 47.0 | 282 | 1.6421 | 0.1220 |
| 1.6243 | 48.0 | 288 | 1.6421 | 0.1220 |
| 1.5633 | 49.0 | 294 | 1.6421 | 0.1220 |
| 1.6091 | 50.0 | 300 | 1.6421 | 0.1220 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1