metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_tiny_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: 0.4540901502504174
smids_5x_deit_tiny_sgd_00001_fold1
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: 1.0635
- Accuracy: 0.4541
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 |
|---|---|---|---|---|
| 1.346 | 1.0 | 376 | 1.2991 | 0.3489 |
| 1.3817 | 2.0 | 752 | 1.2686 | 0.3589 |
| 1.3103 | 3.0 | 1128 | 1.2425 | 0.3656 |
| 1.3556 | 4.0 | 1504 | 1.2205 | 0.3656 |
| 1.2443 | 5.0 | 1880 | 1.2020 | 0.3723 |
| 1.1947 | 6.0 | 2256 | 1.1865 | 0.3806 |
| 1.184 | 7.0 | 2632 | 1.1737 | 0.3940 |
| 1.2121 | 8.0 | 3008 | 1.1630 | 0.3873 |
| 1.1793 | 9.0 | 3384 | 1.1540 | 0.3773 |
| 1.1564 | 10.0 | 3760 | 1.1464 | 0.3740 |
| 1.148 | 11.0 | 4136 | 1.1397 | 0.3756 |
| 1.1774 | 12.0 | 4512 | 1.1340 | 0.3756 |
| 1.1493 | 13.0 | 4888 | 1.1288 | 0.3790 |
| 1.1491 | 14.0 | 5264 | 1.1241 | 0.3790 |
| 1.1465 | 15.0 | 5640 | 1.1198 | 0.3856 |
| 1.1089 | 16.0 | 6016 | 1.1159 | 0.3990 |
| 1.1015 | 17.0 | 6392 | 1.1122 | 0.4057 |
| 1.1166 | 18.0 | 6768 | 1.1086 | 0.4073 |
| 1.1502 | 19.0 | 7144 | 1.1053 | 0.4124 |
| 1.124 | 20.0 | 7520 | 1.1022 | 0.4174 |
| 1.1102 | 21.0 | 7896 | 1.0992 | 0.4207 |
| 1.0904 | 22.0 | 8272 | 1.0964 | 0.4190 |
| 1.0897 | 23.0 | 8648 | 1.0937 | 0.4207 |
| 1.1449 | 24.0 | 9024 | 1.0912 | 0.4190 |
| 1.0609 | 25.0 | 9400 | 1.0888 | 0.4157 |
| 1.0747 | 26.0 | 9776 | 1.0865 | 0.4207 |
| 1.0631 | 27.0 | 10152 | 1.0844 | 0.4240 |
| 1.0872 | 28.0 | 10528 | 1.0823 | 0.4274 |
| 1.0811 | 29.0 | 10904 | 1.0804 | 0.4290 |
| 1.1082 | 30.0 | 11280 | 1.0786 | 0.4307 |
| 1.0863 | 31.0 | 11656 | 1.0769 | 0.4324 |
| 1.103 | 32.0 | 12032 | 1.0753 | 0.4290 |
| 1.0918 | 33.0 | 12408 | 1.0738 | 0.4324 |
| 1.06 | 34.0 | 12784 | 1.0725 | 0.4391 |
| 1.0723 | 35.0 | 13160 | 1.0712 | 0.4424 |
| 1.0366 | 36.0 | 13536 | 1.0701 | 0.4457 |
| 1.0655 | 37.0 | 13912 | 1.0690 | 0.4474 |
| 1.0787 | 38.0 | 14288 | 1.0681 | 0.4457 |
| 1.0751 | 39.0 | 14664 | 1.0672 | 0.4474 |
| 1.0508 | 40.0 | 15040 | 1.0665 | 0.4541 |
| 1.0565 | 41.0 | 15416 | 1.0658 | 0.4541 |
| 1.0404 | 42.0 | 15792 | 1.0652 | 0.4541 |
| 1.0767 | 43.0 | 16168 | 1.0648 | 0.4541 |
| 1.076 | 44.0 | 16544 | 1.0644 | 0.4541 |
| 1.0183 | 45.0 | 16920 | 1.0640 | 0.4541 |
| 1.0393 | 46.0 | 17296 | 1.0638 | 0.4541 |
| 1.065 | 47.0 | 17672 | 1.0636 | 0.4541 |
| 1.0432 | 48.0 | 18048 | 1.0635 | 0.4541 |
| 1.0432 | 49.0 | 18424 | 1.0635 | 0.4541 |
| 1.0255 | 50.0 | 18800 | 1.0635 | 0.4541 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2