metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_tiny_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: 0.2558139534883721
hushem_5x_deit_tiny_sgd_0001_fold3
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: 1.4406
- Accuracy: 0.2558
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 |
|---|---|---|---|---|
| 1.5476 | 1.0 | 28 | 1.6881 | 0.2791 |
| 1.5009 | 2.0 | 56 | 1.6672 | 0.2791 |
| 1.493 | 3.0 | 84 | 1.6491 | 0.2791 |
| 1.4757 | 4.0 | 112 | 1.6326 | 0.2791 |
| 1.4183 | 5.0 | 140 | 1.6168 | 0.2791 |
| 1.4727 | 6.0 | 168 | 1.6027 | 0.2791 |
| 1.5064 | 7.0 | 196 | 1.5899 | 0.2791 |
| 1.4575 | 8.0 | 224 | 1.5786 | 0.2791 |
| 1.4566 | 9.0 | 252 | 1.5679 | 0.3023 |
| 1.4332 | 10.0 | 280 | 1.5586 | 0.3023 |
| 1.4461 | 11.0 | 308 | 1.5502 | 0.3023 |
| 1.4527 | 12.0 | 336 | 1.5422 | 0.3023 |
| 1.4102 | 13.0 | 364 | 1.5344 | 0.3023 |
| 1.4234 | 14.0 | 392 | 1.5271 | 0.3023 |
| 1.4638 | 15.0 | 420 | 1.5205 | 0.3023 |
| 1.4171 | 16.0 | 448 | 1.5148 | 0.3023 |
| 1.3787 | 17.0 | 476 | 1.5087 | 0.2791 |
| 1.4195 | 18.0 | 504 | 1.5032 | 0.2791 |
| 1.3909 | 19.0 | 532 | 1.4981 | 0.3256 |
| 1.4469 | 20.0 | 560 | 1.4935 | 0.3023 |
| 1.382 | 21.0 | 588 | 1.4891 | 0.3023 |
| 1.3548 | 22.0 | 616 | 1.4852 | 0.3023 |
| 1.4115 | 23.0 | 644 | 1.4815 | 0.3023 |
| 1.3595 | 24.0 | 672 | 1.4779 | 0.2791 |
| 1.4648 | 25.0 | 700 | 1.4744 | 0.2791 |
| 1.3584 | 26.0 | 728 | 1.4712 | 0.2791 |
| 1.3694 | 27.0 | 756 | 1.4682 | 0.2791 |
| 1.3704 | 28.0 | 784 | 1.4656 | 0.2791 |
| 1.3747 | 29.0 | 812 | 1.4631 | 0.2791 |
| 1.3528 | 30.0 | 840 | 1.4609 | 0.2791 |
| 1.3372 | 31.0 | 868 | 1.4586 | 0.2791 |
| 1.3782 | 32.0 | 896 | 1.4565 | 0.2791 |
| 1.3746 | 33.0 | 924 | 1.4545 | 0.2791 |
| 1.3597 | 34.0 | 952 | 1.4525 | 0.2791 |
| 1.3491 | 35.0 | 980 | 1.4509 | 0.2791 |
| 1.3872 | 36.0 | 1008 | 1.4493 | 0.2791 |
| 1.3595 | 37.0 | 1036 | 1.4478 | 0.2791 |
| 1.3401 | 38.0 | 1064 | 1.4465 | 0.2791 |
| 1.3573 | 39.0 | 1092 | 1.4454 | 0.2791 |
| 1.3488 | 40.0 | 1120 | 1.4444 | 0.2791 |
| 1.3842 | 41.0 | 1148 | 1.4435 | 0.2791 |
| 1.3433 | 42.0 | 1176 | 1.4428 | 0.2558 |
| 1.3592 | 43.0 | 1204 | 1.4421 | 0.2558 |
| 1.3773 | 44.0 | 1232 | 1.4415 | 0.2558 |
| 1.3285 | 45.0 | 1260 | 1.4411 | 0.2558 |
| 1.3374 | 46.0 | 1288 | 1.4408 | 0.2558 |
| 1.3383 | 47.0 | 1316 | 1.4407 | 0.2558 |
| 1.3567 | 48.0 | 1344 | 1.4406 | 0.2558 |
| 1.3494 | 49.0 | 1372 | 1.4406 | 0.2558 |
| 1.2617 | 50.0 | 1400 | 1.4406 | 0.2558 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0