metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_base_rms_001_fold5
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: 0.7560975609756098
hushem_40x_deit_base_rms_001_fold5
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: 3.5781
- Accuracy: 0.7561
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: 0.001
- 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 |
|---|---|---|---|---|
| 1.2271 | 1.0 | 220 | 1.5032 | 0.3902 |
| 0.9545 | 2.0 | 440 | 1.5087 | 0.3902 |
| 0.8667 | 3.0 | 660 | 1.0714 | 0.4878 |
| 0.8154 | 4.0 | 880 | 0.7851 | 0.6098 |
| 0.6309 | 5.0 | 1100 | 1.0215 | 0.4878 |
| 0.5655 | 6.0 | 1320 | 0.8556 | 0.6098 |
| 0.4033 | 7.0 | 1540 | 0.7849 | 0.7073 |
| 0.3567 | 8.0 | 1760 | 1.1431 | 0.6585 |
| 0.3869 | 9.0 | 1980 | 0.7273 | 0.7561 |
| 0.2867 | 10.0 | 2200 | 0.9025 | 0.6341 |
| 0.2933 | 11.0 | 2420 | 1.0767 | 0.6829 |
| 0.2822 | 12.0 | 2640 | 0.9054 | 0.7561 |
| 0.2576 | 13.0 | 2860 | 1.1701 | 0.7073 |
| 0.1424 | 14.0 | 3080 | 1.2265 | 0.7317 |
| 0.1597 | 15.0 | 3300 | 1.2021 | 0.7317 |
| 0.0822 | 16.0 | 3520 | 1.5652 | 0.7073 |
| 0.0859 | 17.0 | 3740 | 1.0512 | 0.7561 |
| 0.1048 | 18.0 | 3960 | 1.9377 | 0.6341 |
| 0.0506 | 19.0 | 4180 | 1.4302 | 0.7561 |
| 0.0595 | 20.0 | 4400 | 1.2065 | 0.7073 |
| 0.1492 | 21.0 | 4620 | 1.7891 | 0.7073 |
| 0.0835 | 22.0 | 4840 | 1.5550 | 0.7561 |
| 0.0475 | 23.0 | 5060 | 1.2142 | 0.7317 |
| 0.0941 | 24.0 | 5280 | 1.4080 | 0.7073 |
| 0.0186 | 25.0 | 5500 | 1.5889 | 0.7561 |
| 0.0776 | 26.0 | 5720 | 1.8453 | 0.6829 |
| 0.0752 | 27.0 | 5940 | 1.5817 | 0.7805 |
| 0.0113 | 28.0 | 6160 | 1.6776 | 0.7805 |
| 0.0011 | 29.0 | 6380 | 2.1296 | 0.7317 |
| 0.0107 | 30.0 | 6600 | 1.9807 | 0.7073 |
| 0.0181 | 31.0 | 6820 | 1.9248 | 0.7073 |
| 0.0106 | 32.0 | 7040 | 2.5784 | 0.7317 |
| 0.0002 | 33.0 | 7260 | 1.8180 | 0.8049 |
| 0.0013 | 34.0 | 7480 | 1.5976 | 0.8049 |
| 0.0031 | 35.0 | 7700 | 1.9747 | 0.7317 |
| 0.0094 | 36.0 | 7920 | 2.4830 | 0.7317 |
| 0.0006 | 37.0 | 8140 | 2.9074 | 0.7561 |
| 0.0049 | 38.0 | 8360 | 2.6503 | 0.6829 |
| 0.0002 | 39.0 | 8580 | 2.4189 | 0.7561 |
| 0.0 | 40.0 | 8800 | 2.4124 | 0.7561 |
| 0.0 | 41.0 | 9020 | 2.5470 | 0.7561 |
| 0.0 | 42.0 | 9240 | 2.6196 | 0.7805 |
| 0.0 | 43.0 | 9460 | 2.7251 | 0.7805 |
| 0.0 | 44.0 | 9680 | 2.9457 | 0.7805 |
| 0.0 | 45.0 | 9900 | 3.1311 | 0.7805 |
| 0.0 | 46.0 | 10120 | 3.2547 | 0.7805 |
| 0.0 | 47.0 | 10340 | 3.3567 | 0.7317 |
| 0.0 | 48.0 | 10560 | 3.5689 | 0.7561 |
| 0.0 | 49.0 | 10780 | 3.5825 | 0.7561 |
| 0.0 | 50.0 | 11000 | 3.5781 | 0.7561 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2