metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_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: 0.46511627906976744
hushem_40x_deit_base_sgd_0001_fold3
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.2710
- Accuracy: 0.4651
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 |
|---|---|---|---|---|
| 1.3787 | 1.0 | 217 | 1.4567 | 0.2326 |
| 1.3411 | 2.0 | 434 | 1.4476 | 0.2326 |
| 1.3346 | 3.0 | 651 | 1.4398 | 0.2326 |
| 1.3522 | 4.0 | 868 | 1.4325 | 0.2558 |
| 1.295 | 5.0 | 1085 | 1.4257 | 0.2558 |
| 1.3027 | 6.0 | 1302 | 1.4192 | 0.2791 |
| 1.2908 | 7.0 | 1519 | 1.4129 | 0.3023 |
| 1.2684 | 8.0 | 1736 | 1.4068 | 0.3023 |
| 1.2597 | 9.0 | 1953 | 1.4007 | 0.3023 |
| 1.2504 | 10.0 | 2170 | 1.3948 | 0.3023 |
| 1.2181 | 11.0 | 2387 | 1.3891 | 0.3023 |
| 1.2286 | 12.0 | 2604 | 1.3834 | 0.3023 |
| 1.229 | 13.0 | 2821 | 1.3779 | 0.3023 |
| 1.2118 | 14.0 | 3038 | 1.3725 | 0.3256 |
| 1.1939 | 15.0 | 3255 | 1.3673 | 0.3256 |
| 1.2054 | 16.0 | 3472 | 1.3622 | 0.3488 |
| 1.1836 | 17.0 | 3689 | 1.3572 | 0.3721 |
| 1.1754 | 18.0 | 3906 | 1.3524 | 0.3721 |
| 1.1872 | 19.0 | 4123 | 1.3477 | 0.3721 |
| 1.1652 | 20.0 | 4340 | 1.3431 | 0.3721 |
| 1.1396 | 21.0 | 4557 | 1.3387 | 0.3721 |
| 1.1373 | 22.0 | 4774 | 1.3343 | 0.3953 |
| 1.1381 | 23.0 | 4991 | 1.3300 | 0.3953 |
| 1.101 | 24.0 | 5208 | 1.3259 | 0.3953 |
| 1.1305 | 25.0 | 5425 | 1.3219 | 0.4186 |
| 1.1458 | 26.0 | 5642 | 1.3181 | 0.4186 |
| 1.0969 | 27.0 | 5859 | 1.3143 | 0.4186 |
| 1.092 | 28.0 | 6076 | 1.3106 | 0.4186 |
| 1.0422 | 29.0 | 6293 | 1.3071 | 0.4186 |
| 1.07 | 30.0 | 6510 | 1.3037 | 0.4419 |
| 1.097 | 31.0 | 6727 | 1.3005 | 0.4419 |
| 1.1048 | 32.0 | 6944 | 1.2974 | 0.4419 |
| 1.0657 | 33.0 | 7161 | 1.2945 | 0.4419 |
| 1.0841 | 34.0 | 7378 | 1.2918 | 0.4419 |
| 1.0697 | 35.0 | 7595 | 1.2891 | 0.4419 |
| 1.0586 | 36.0 | 7812 | 1.2867 | 0.4419 |
| 1.0346 | 37.0 | 8029 | 1.2845 | 0.4419 |
| 1.0364 | 38.0 | 8246 | 1.2824 | 0.4651 |
| 1.055 | 39.0 | 8463 | 1.2804 | 0.4651 |
| 1.0391 | 40.0 | 8680 | 1.2787 | 0.4651 |
| 1.0408 | 41.0 | 8897 | 1.2771 | 0.4651 |
| 1.0911 | 42.0 | 9114 | 1.2757 | 0.4651 |
| 1.042 | 43.0 | 9331 | 1.2745 | 0.4651 |
| 1.0562 | 44.0 | 9548 | 1.2735 | 0.4651 |
| 1.0444 | 45.0 | 9765 | 1.2727 | 0.4651 |
| 1.0551 | 46.0 | 9982 | 1.2720 | 0.4651 |
| 1.0314 | 47.0 | 10199 | 1.2715 | 0.4651 |
| 1.067 | 48.0 | 10416 | 1.2712 | 0.4651 |
| 1.0573 | 49.0 | 10633 | 1.2710 | 0.4651 |
| 1.0022 | 50.0 | 10850 | 1.2710 | 0.4651 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2