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_fold4
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: 0.38095238095238093
hushem_5x_deit_tiny_sgd_0001_fold4
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: 1.3803
- Accuracy: 0.3810
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 |
|---|---|---|---|---|
| 1.509 | 1.0 | 28 | 1.6728 | 0.2857 |
| 1.4745 | 2.0 | 56 | 1.6494 | 0.2857 |
| 1.4631 | 3.0 | 84 | 1.6263 | 0.2857 |
| 1.4901 | 4.0 | 112 | 1.6063 | 0.2857 |
| 1.441 | 5.0 | 140 | 1.5891 | 0.2857 |
| 1.4757 | 6.0 | 168 | 1.5714 | 0.2857 |
| 1.4394 | 7.0 | 196 | 1.5560 | 0.2857 |
| 1.4378 | 8.0 | 224 | 1.5417 | 0.2857 |
| 1.4304 | 9.0 | 252 | 1.5286 | 0.2857 |
| 1.455 | 10.0 | 280 | 1.5162 | 0.2857 |
| 1.4518 | 11.0 | 308 | 1.5058 | 0.2857 |
| 1.4092 | 12.0 | 336 | 1.4955 | 0.3095 |
| 1.4226 | 13.0 | 364 | 1.4865 | 0.3095 |
| 1.3993 | 14.0 | 392 | 1.4783 | 0.3095 |
| 1.3967 | 15.0 | 420 | 1.4705 | 0.3095 |
| 1.411 | 16.0 | 448 | 1.4633 | 0.3095 |
| 1.4285 | 17.0 | 476 | 1.4567 | 0.3095 |
| 1.3979 | 18.0 | 504 | 1.4501 | 0.3333 |
| 1.3856 | 19.0 | 532 | 1.4445 | 0.3333 |
| 1.3836 | 20.0 | 560 | 1.4396 | 0.3333 |
| 1.3724 | 21.0 | 588 | 1.4346 | 0.3333 |
| 1.4133 | 22.0 | 616 | 1.4302 | 0.3333 |
| 1.3803 | 23.0 | 644 | 1.4261 | 0.3571 |
| 1.38 | 24.0 | 672 | 1.4220 | 0.3571 |
| 1.3524 | 25.0 | 700 | 1.4181 | 0.3571 |
| 1.3732 | 26.0 | 728 | 1.4145 | 0.3571 |
| 1.3766 | 27.0 | 756 | 1.4110 | 0.3571 |
| 1.3865 | 28.0 | 784 | 1.4081 | 0.3571 |
| 1.3436 | 29.0 | 812 | 1.4052 | 0.3571 |
| 1.3611 | 30.0 | 840 | 1.4024 | 0.3571 |
| 1.3712 | 31.0 | 868 | 1.3999 | 0.3571 |
| 1.3547 | 32.0 | 896 | 1.3975 | 0.3571 |
| 1.3736 | 33.0 | 924 | 1.3953 | 0.3571 |
| 1.3568 | 34.0 | 952 | 1.3933 | 0.3571 |
| 1.3531 | 35.0 | 980 | 1.3914 | 0.3571 |
| 1.3544 | 36.0 | 1008 | 1.3897 | 0.3571 |
| 1.3181 | 37.0 | 1036 | 1.3881 | 0.3571 |
| 1.3538 | 38.0 | 1064 | 1.3867 | 0.3571 |
| 1.3828 | 39.0 | 1092 | 1.3855 | 0.3810 |
| 1.3242 | 40.0 | 1120 | 1.3844 | 0.3810 |
| 1.3519 | 41.0 | 1148 | 1.3834 | 0.3810 |
| 1.3218 | 42.0 | 1176 | 1.3826 | 0.3810 |
| 1.3603 | 43.0 | 1204 | 1.3819 | 0.3810 |
| 1.3249 | 44.0 | 1232 | 1.3813 | 0.3810 |
| 1.3333 | 45.0 | 1260 | 1.3809 | 0.3810 |
| 1.3432 | 46.0 | 1288 | 1.3806 | 0.3810 |
| 1.333 | 47.0 | 1316 | 1.3804 | 0.3810 |
| 1.3303 | 48.0 | 1344 | 1.3803 | 0.3810 |
| 1.3729 | 49.0 | 1372 | 1.3803 | 0.3810 |
| 1.3281 | 50.0 | 1400 | 1.3803 | 0.3810 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0