metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_deit_base_sgd_00001_fold1
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: 0.44908180300500833
smids_3x_deit_base_sgd_00001_fold1
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: 1.0659
- Accuracy: 0.4491
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 |
|---|---|---|---|---|
| 1.1289 | 1.0 | 226 | 1.0936 | 0.3873 |
| 1.088 | 2.0 | 452 | 1.0923 | 0.3907 |
| 1.1393 | 3.0 | 678 | 1.0911 | 0.3940 |
| 1.1082 | 4.0 | 904 | 1.0899 | 0.3957 |
| 1.1039 | 5.0 | 1130 | 1.0887 | 0.3973 |
| 1.1198 | 6.0 | 1356 | 1.0876 | 0.3957 |
| 1.1055 | 7.0 | 1582 | 1.0865 | 0.3957 |
| 1.1209 | 8.0 | 1808 | 1.0854 | 0.3973 |
| 1.0984 | 9.0 | 2034 | 1.0844 | 0.3990 |
| 1.0834 | 10.0 | 2260 | 1.0834 | 0.4040 |
| 1.1107 | 11.0 | 2486 | 1.0825 | 0.4057 |
| 1.1106 | 12.0 | 2712 | 1.0815 | 0.4107 |
| 1.0951 | 13.0 | 2938 | 1.0807 | 0.4107 |
| 1.084 | 14.0 | 3164 | 1.0798 | 0.4140 |
| 1.0913 | 15.0 | 3390 | 1.0790 | 0.4224 |
| 1.0879 | 16.0 | 3616 | 1.0781 | 0.4274 |
| 1.0942 | 17.0 | 3842 | 1.0774 | 0.4290 |
| 1.1034 | 18.0 | 4068 | 1.0766 | 0.4290 |
| 1.0749 | 19.0 | 4294 | 1.0759 | 0.4290 |
| 1.0856 | 20.0 | 4520 | 1.0752 | 0.4341 |
| 1.0907 | 21.0 | 4746 | 1.0745 | 0.4407 |
| 1.0776 | 22.0 | 4972 | 1.0739 | 0.4424 |
| 1.0863 | 23.0 | 5198 | 1.0733 | 0.4407 |
| 1.0887 | 24.0 | 5424 | 1.0727 | 0.4424 |
| 1.0775 | 25.0 | 5650 | 1.0722 | 0.4474 |
| 1.092 | 26.0 | 5876 | 1.0716 | 0.4457 |
| 1.09 | 27.0 | 6102 | 1.0711 | 0.4424 |
| 1.0932 | 28.0 | 6328 | 1.0707 | 0.4391 |
| 1.0761 | 29.0 | 6554 | 1.0702 | 0.4407 |
| 1.0937 | 30.0 | 6780 | 1.0698 | 0.4407 |
| 1.0661 | 31.0 | 7006 | 1.0694 | 0.4424 |
| 1.0826 | 32.0 | 7232 | 1.0690 | 0.4424 |
| 1.0898 | 33.0 | 7458 | 1.0686 | 0.4407 |
| 1.0784 | 34.0 | 7684 | 1.0683 | 0.4457 |
| 1.0944 | 35.0 | 7910 | 1.0680 | 0.4457 |
| 1.08 | 36.0 | 8136 | 1.0677 | 0.4474 |
| 1.0796 | 37.0 | 8362 | 1.0674 | 0.4474 |
| 1.08 | 38.0 | 8588 | 1.0672 | 0.4491 |
| 1.0835 | 39.0 | 8814 | 1.0670 | 0.4491 |
| 1.0952 | 40.0 | 9040 | 1.0668 | 0.4491 |
| 1.0844 | 41.0 | 9266 | 1.0666 | 0.4474 |
| 1.0907 | 42.0 | 9492 | 1.0664 | 0.4474 |
| 1.087 | 43.0 | 9718 | 1.0663 | 0.4474 |
| 1.0798 | 44.0 | 9944 | 1.0662 | 0.4474 |
| 1.0672 | 45.0 | 10170 | 1.0661 | 0.4457 |
| 1.0874 | 46.0 | 10396 | 1.0660 | 0.4457 |
| 1.0866 | 47.0 | 10622 | 1.0660 | 0.4457 |
| 1.0871 | 48.0 | 10848 | 1.0660 | 0.4474 |
| 1.0775 | 49.0 | 11074 | 1.0659 | 0.4491 |
| 1.0886 | 50.0 | 11300 | 1.0659 | 0.4491 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2