metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_sgd_001_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: 0.4444444444444444
hushem_5x_deit_small_sgd_001_fold2
This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.3629
- Accuracy: 0.4444
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 |
|---|---|---|---|---|
| 1.4659 | 1.0 | 27 | 1.4409 | 0.2889 |
| 1.3866 | 2.0 | 54 | 1.4026 | 0.3556 |
| 1.3486 | 3.0 | 81 | 1.3816 | 0.3333 |
| 1.3477 | 4.0 | 108 | 1.3676 | 0.3111 |
| 1.2816 | 5.0 | 135 | 1.3557 | 0.3333 |
| 1.2558 | 6.0 | 162 | 1.3444 | 0.3556 |
| 1.2259 | 7.0 | 189 | 1.3343 | 0.3556 |
| 1.2042 | 8.0 | 216 | 1.3245 | 0.3556 |
| 1.1683 | 9.0 | 243 | 1.3158 | 0.4 |
| 1.1515 | 10.0 | 270 | 1.3086 | 0.4222 |
| 1.1156 | 11.0 | 297 | 1.3037 | 0.4222 |
| 1.1061 | 12.0 | 324 | 1.2999 | 0.4444 |
| 1.0903 | 13.0 | 351 | 1.3002 | 0.4444 |
| 1.0661 | 14.0 | 378 | 1.3028 | 0.4444 |
| 1.0598 | 15.0 | 405 | 1.3085 | 0.4444 |
| 1.0378 | 16.0 | 432 | 1.3130 | 0.4444 |
| 1.0191 | 17.0 | 459 | 1.3179 | 0.4444 |
| 0.9884 | 18.0 | 486 | 1.3238 | 0.4444 |
| 0.9629 | 19.0 | 513 | 1.3282 | 0.4444 |
| 0.9575 | 20.0 | 540 | 1.3319 | 0.4222 |
| 0.9397 | 21.0 | 567 | 1.3353 | 0.4222 |
| 0.9296 | 22.0 | 594 | 1.3380 | 0.4222 |
| 0.9149 | 23.0 | 621 | 1.3408 | 0.4222 |
| 0.9023 | 24.0 | 648 | 1.3446 | 0.4222 |
| 0.8747 | 25.0 | 675 | 1.3454 | 0.4667 |
| 0.9184 | 26.0 | 702 | 1.3472 | 0.4444 |
| 0.8454 | 27.0 | 729 | 1.3479 | 0.4444 |
| 0.8505 | 28.0 | 756 | 1.3510 | 0.4444 |
| 0.8567 | 29.0 | 783 | 1.3517 | 0.4444 |
| 0.8854 | 30.0 | 810 | 1.3544 | 0.4667 |
| 0.834 | 31.0 | 837 | 1.3546 | 0.4444 |
| 0.8438 | 32.0 | 864 | 1.3560 | 0.4444 |
| 0.8236 | 33.0 | 891 | 1.3564 | 0.4444 |
| 0.8208 | 34.0 | 918 | 1.3570 | 0.4444 |
| 0.8066 | 35.0 | 945 | 1.3589 | 0.4444 |
| 0.8073 | 36.0 | 972 | 1.3591 | 0.4444 |
| 0.8089 | 37.0 | 999 | 1.3595 | 0.4444 |
| 0.777 | 38.0 | 1026 | 1.3599 | 0.4444 |
| 0.7828 | 39.0 | 1053 | 1.3610 | 0.4444 |
| 0.787 | 40.0 | 1080 | 1.3609 | 0.4444 |
| 0.8016 | 41.0 | 1107 | 1.3612 | 0.4444 |
| 0.7822 | 42.0 | 1134 | 1.3619 | 0.4444 |
| 0.8105 | 43.0 | 1161 | 1.3621 | 0.4444 |
| 0.7646 | 44.0 | 1188 | 1.3622 | 0.4444 |
| 0.7928 | 45.0 | 1215 | 1.3624 | 0.4444 |
| 0.7714 | 46.0 | 1242 | 1.3625 | 0.4444 |
| 0.7741 | 47.0 | 1269 | 1.3627 | 0.4444 |
| 0.7688 | 48.0 | 1296 | 1.3629 | 0.4444 |
| 0.834 | 49.0 | 1323 | 1.3629 | 0.4444 |
| 0.7751 | 50.0 | 1350 | 1.3629 | 0.4444 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0