metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_small_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: 0.2619047619047619
hushem_5x_deit_small_sgd_0001_fold4
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: 1.3721
- Accuracy: 0.2619
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 |
|---|---|---|---|---|
| 1.5364 | 1.0 | 28 | 1.4759 | 0.2857 |
| 1.6032 | 2.0 | 56 | 1.4677 | 0.2857 |
| 1.5235 | 3.0 | 84 | 1.4598 | 0.2857 |
| 1.5363 | 4.0 | 112 | 1.4530 | 0.2857 |
| 1.4963 | 5.0 | 140 | 1.4466 | 0.2857 |
| 1.4798 | 6.0 | 168 | 1.4404 | 0.2857 |
| 1.4963 | 7.0 | 196 | 1.4349 | 0.2857 |
| 1.441 | 8.0 | 224 | 1.4297 | 0.3095 |
| 1.5032 | 9.0 | 252 | 1.4249 | 0.3095 |
| 1.4231 | 10.0 | 280 | 1.4205 | 0.3095 |
| 1.4482 | 11.0 | 308 | 1.4164 | 0.3095 |
| 1.4398 | 12.0 | 336 | 1.4127 | 0.3095 |
| 1.468 | 13.0 | 364 | 1.4093 | 0.3095 |
| 1.4278 | 14.0 | 392 | 1.4061 | 0.3095 |
| 1.4624 | 15.0 | 420 | 1.4032 | 0.3095 |
| 1.438 | 16.0 | 448 | 1.4004 | 0.2857 |
| 1.4401 | 17.0 | 476 | 1.3979 | 0.2857 |
| 1.416 | 18.0 | 504 | 1.3956 | 0.3095 |
| 1.4033 | 19.0 | 532 | 1.3934 | 0.3333 |
| 1.4123 | 20.0 | 560 | 1.3916 | 0.3333 |
| 1.4056 | 21.0 | 588 | 1.3899 | 0.3095 |
| 1.4089 | 22.0 | 616 | 1.3883 | 0.3333 |
| 1.3801 | 23.0 | 644 | 1.3868 | 0.3333 |
| 1.3733 | 24.0 | 672 | 1.3854 | 0.3095 |
| 1.3798 | 25.0 | 700 | 1.3840 | 0.3095 |
| 1.4051 | 26.0 | 728 | 1.3828 | 0.3095 |
| 1.4017 | 27.0 | 756 | 1.3817 | 0.3095 |
| 1.4006 | 28.0 | 784 | 1.3807 | 0.3095 |
| 1.368 | 29.0 | 812 | 1.3797 | 0.3095 |
| 1.3628 | 30.0 | 840 | 1.3788 | 0.3333 |
| 1.3803 | 31.0 | 868 | 1.3780 | 0.2619 |
| 1.3495 | 32.0 | 896 | 1.3773 | 0.2619 |
| 1.393 | 33.0 | 924 | 1.3766 | 0.2619 |
| 1.3379 | 34.0 | 952 | 1.3760 | 0.2619 |
| 1.3609 | 35.0 | 980 | 1.3754 | 0.2619 |
| 1.3521 | 36.0 | 1008 | 1.3748 | 0.2619 |
| 1.3648 | 37.0 | 1036 | 1.3744 | 0.2619 |
| 1.341 | 38.0 | 1064 | 1.3740 | 0.2619 |
| 1.3689 | 39.0 | 1092 | 1.3736 | 0.2619 |
| 1.3877 | 40.0 | 1120 | 1.3733 | 0.2619 |
| 1.4062 | 41.0 | 1148 | 1.3730 | 0.2619 |
| 1.3585 | 42.0 | 1176 | 1.3727 | 0.2619 |
| 1.3339 | 43.0 | 1204 | 1.3725 | 0.2619 |
| 1.3351 | 44.0 | 1232 | 1.3724 | 0.2619 |
| 1.3978 | 45.0 | 1260 | 1.3722 | 0.2619 |
| 1.3819 | 46.0 | 1288 | 1.3721 | 0.2619 |
| 1.3511 | 47.0 | 1316 | 1.3721 | 0.2619 |
| 1.3593 | 48.0 | 1344 | 1.3721 | 0.2619 |
| 1.3691 | 49.0 | 1372 | 1.3721 | 0.2619 |
| 1.3757 | 50.0 | 1400 | 1.3721 | 0.2619 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0