metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_sgd_0001_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: 0.13333333333333333
hushem_5x_deit_base_sgd_0001_fold2
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: 1.4239
- Accuracy: 0.1333
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 |
---|---|---|---|---|
1.43 | 1.0 | 27 | 1.4766 | 0.1333 |
1.4102 | 2.0 | 54 | 1.4737 | 0.1333 |
1.4007 | 3.0 | 81 | 1.4709 | 0.1333 |
1.4122 | 4.0 | 108 | 1.4682 | 0.1333 |
1.4031 | 5.0 | 135 | 1.4658 | 0.1333 |
1.4094 | 6.0 | 162 | 1.4633 | 0.1333 |
1.3941 | 7.0 | 189 | 1.4611 | 0.1333 |
1.4105 | 8.0 | 216 | 1.4588 | 0.1333 |
1.4006 | 9.0 | 243 | 1.4567 | 0.1333 |
1.3895 | 10.0 | 270 | 1.4547 | 0.1333 |
1.3922 | 11.0 | 297 | 1.4528 | 0.1333 |
1.3661 | 12.0 | 324 | 1.4510 | 0.1333 |
1.397 | 13.0 | 351 | 1.4492 | 0.1333 |
1.3778 | 14.0 | 378 | 1.4476 | 0.1333 |
1.3888 | 15.0 | 405 | 1.4461 | 0.1333 |
1.3865 | 16.0 | 432 | 1.4446 | 0.1333 |
1.3782 | 17.0 | 459 | 1.4432 | 0.1333 |
1.3766 | 18.0 | 486 | 1.4418 | 0.1333 |
1.3767 | 19.0 | 513 | 1.4404 | 0.1333 |
1.3782 | 20.0 | 540 | 1.4392 | 0.1333 |
1.3664 | 21.0 | 567 | 1.4381 | 0.1333 |
1.3644 | 22.0 | 594 | 1.4370 | 0.1333 |
1.386 | 23.0 | 621 | 1.4359 | 0.1333 |
1.3679 | 24.0 | 648 | 1.4349 | 0.1333 |
1.3604 | 25.0 | 675 | 1.4339 | 0.1333 |
1.3727 | 26.0 | 702 | 1.4330 | 0.1333 |
1.3624 | 27.0 | 729 | 1.4321 | 0.1333 |
1.3512 | 28.0 | 756 | 1.4313 | 0.1333 |
1.3641 | 29.0 | 783 | 1.4305 | 0.1333 |
1.3697 | 30.0 | 810 | 1.4298 | 0.1333 |
1.3661 | 31.0 | 837 | 1.4292 | 0.1333 |
1.3762 | 32.0 | 864 | 1.4286 | 0.1333 |
1.3653 | 33.0 | 891 | 1.4280 | 0.1333 |
1.3526 | 34.0 | 918 | 1.4274 | 0.1333 |
1.3565 | 35.0 | 945 | 1.4269 | 0.1333 |
1.3671 | 36.0 | 972 | 1.4265 | 0.1333 |
1.3721 | 37.0 | 999 | 1.4261 | 0.1333 |
1.3579 | 38.0 | 1026 | 1.4257 | 0.1333 |
1.3662 | 39.0 | 1053 | 1.4254 | 0.1333 |
1.3491 | 40.0 | 1080 | 1.4250 | 0.1333 |
1.3508 | 41.0 | 1107 | 1.4248 | 0.1333 |
1.3555 | 42.0 | 1134 | 1.4245 | 0.1333 |
1.3427 | 43.0 | 1161 | 1.4244 | 0.1333 |
1.3543 | 44.0 | 1188 | 1.4242 | 0.1333 |
1.3592 | 45.0 | 1215 | 1.4241 | 0.1333 |
1.3632 | 46.0 | 1242 | 1.4240 | 0.1333 |
1.3606 | 47.0 | 1269 | 1.4239 | 0.1333 |
1.3593 | 48.0 | 1296 | 1.4239 | 0.1333 |
1.3726 | 49.0 | 1323 | 1.4239 | 0.1333 |
1.3608 | 50.0 | 1350 | 1.4239 | 0.1333 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0