metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_sgd_00001_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: 0.32558139534883723
hushem_40x_deit_small_sgd_00001_fold3
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: 1.3703
- Accuracy: 0.3256
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 |
|---|---|---|---|---|
| 1.8914 | 1.0 | 217 | 1.5805 | 0.2558 |
| 2.0178 | 2.0 | 434 | 1.5654 | 0.2558 |
| 2.0179 | 3.0 | 651 | 1.5510 | 0.2558 |
| 1.8888 | 4.0 | 868 | 1.5374 | 0.2558 |
| 1.872 | 5.0 | 1085 | 1.5245 | 0.2558 |
| 1.7831 | 6.0 | 1302 | 1.5124 | 0.2558 |
| 1.836 | 7.0 | 1519 | 1.5009 | 0.2558 |
| 1.8178 | 8.0 | 1736 | 1.4901 | 0.2558 |
| 1.7694 | 9.0 | 1953 | 1.4801 | 0.2326 |
| 1.7678 | 10.0 | 2170 | 1.4706 | 0.2326 |
| 1.659 | 11.0 | 2387 | 1.4618 | 0.2326 |
| 1.6239 | 12.0 | 2604 | 1.4536 | 0.2558 |
| 1.6882 | 13.0 | 2821 | 1.4460 | 0.2558 |
| 1.6748 | 14.0 | 3038 | 1.4391 | 0.2558 |
| 1.6892 | 15.0 | 3255 | 1.4327 | 0.2791 |
| 1.725 | 16.0 | 3472 | 1.4268 | 0.2791 |
| 1.6371 | 17.0 | 3689 | 1.4214 | 0.2791 |
| 1.6193 | 18.0 | 3906 | 1.4164 | 0.3256 |
| 1.6512 | 19.0 | 4123 | 1.4119 | 0.3256 |
| 1.6188 | 20.0 | 4340 | 1.4078 | 0.3256 |
| 1.643 | 21.0 | 4557 | 1.4041 | 0.3256 |
| 1.5803 | 22.0 | 4774 | 1.4006 | 0.3256 |
| 1.592 | 23.0 | 4991 | 1.3975 | 0.3256 |
| 1.5987 | 24.0 | 5208 | 1.3946 | 0.3256 |
| 1.566 | 25.0 | 5425 | 1.3921 | 0.3488 |
| 1.5574 | 26.0 | 5642 | 1.3897 | 0.3488 |
| 1.4978 | 27.0 | 5859 | 1.3876 | 0.3488 |
| 1.524 | 28.0 | 6076 | 1.3857 | 0.3488 |
| 1.5682 | 29.0 | 6293 | 1.3839 | 0.3488 |
| 1.5042 | 30.0 | 6510 | 1.3823 | 0.3488 |
| 1.5589 | 31.0 | 6727 | 1.3808 | 0.3023 |
| 1.5347 | 32.0 | 6944 | 1.3795 | 0.3023 |
| 1.5403 | 33.0 | 7161 | 1.3783 | 0.3023 |
| 1.5548 | 34.0 | 7378 | 1.3772 | 0.3023 |
| 1.5321 | 35.0 | 7595 | 1.3762 | 0.3023 |
| 1.5015 | 36.0 | 7812 | 1.3753 | 0.3023 |
| 1.4993 | 37.0 | 8029 | 1.3745 | 0.3023 |
| 1.4844 | 38.0 | 8246 | 1.3738 | 0.3023 |
| 1.5191 | 39.0 | 8463 | 1.3732 | 0.3023 |
| 1.515 | 40.0 | 8680 | 1.3726 | 0.3256 |
| 1.4957 | 41.0 | 8897 | 1.3721 | 0.3256 |
| 1.5585 | 42.0 | 9114 | 1.3717 | 0.3256 |
| 1.5037 | 43.0 | 9331 | 1.3713 | 0.3256 |
| 1.4828 | 44.0 | 9548 | 1.3710 | 0.3256 |
| 1.4967 | 45.0 | 9765 | 1.3708 | 0.3256 |
| 1.5387 | 46.0 | 9982 | 1.3706 | 0.3256 |
| 1.5118 | 47.0 | 10199 | 1.3705 | 0.3256 |
| 1.5073 | 48.0 | 10416 | 1.3704 | 0.3256 |
| 1.5166 | 49.0 | 10633 | 1.3703 | 0.3256 |
| 1.4994 | 50.0 | 10850 | 1.3703 | 0.3256 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2