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_sgd_0001_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: 0.5121951219512195
hushem_40x_deit_base_sgd_0001_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: 1.1678
- Accuracy: 0.5122
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 |
|---|---|---|---|---|
| 1.3902 | 1.0 | 220 | 1.3668 | 0.2683 |
| 1.375 | 2.0 | 440 | 1.3610 | 0.2927 |
| 1.3643 | 3.0 | 660 | 1.3560 | 0.2683 |
| 1.3352 | 4.0 | 880 | 1.3513 | 0.2683 |
| 1.343 | 5.0 | 1100 | 1.3466 | 0.2683 |
| 1.2985 | 6.0 | 1320 | 1.3416 | 0.2683 |
| 1.3152 | 7.0 | 1540 | 1.3365 | 0.2927 |
| 1.2618 | 8.0 | 1760 | 1.3311 | 0.3171 |
| 1.2728 | 9.0 | 1980 | 1.3254 | 0.3415 |
| 1.2604 | 10.0 | 2200 | 1.3195 | 0.3415 |
| 1.2446 | 11.0 | 2420 | 1.3136 | 0.3415 |
| 1.2322 | 12.0 | 2640 | 1.3076 | 0.3902 |
| 1.2519 | 13.0 | 2860 | 1.3017 | 0.4146 |
| 1.2115 | 14.0 | 3080 | 1.2958 | 0.4146 |
| 1.2112 | 15.0 | 3300 | 1.2899 | 0.4390 |
| 1.1892 | 16.0 | 3520 | 1.2841 | 0.4390 |
| 1.1942 | 17.0 | 3740 | 1.2784 | 0.4390 |
| 1.2008 | 18.0 | 3960 | 1.2727 | 0.4390 |
| 1.1853 | 19.0 | 4180 | 1.2671 | 0.4390 |
| 1.1573 | 20.0 | 4400 | 1.2615 | 0.4634 |
| 1.1577 | 21.0 | 4620 | 1.2560 | 0.4634 |
| 1.1317 | 22.0 | 4840 | 1.2506 | 0.4634 |
| 1.1597 | 23.0 | 5060 | 1.2453 | 0.4878 |
| 1.1283 | 24.0 | 5280 | 1.2401 | 0.4878 |
| 1.1168 | 25.0 | 5500 | 1.2349 | 0.4634 |
| 1.142 | 26.0 | 5720 | 1.2300 | 0.4634 |
| 1.1324 | 27.0 | 5940 | 1.2251 | 0.4634 |
| 1.1074 | 28.0 | 6160 | 1.2203 | 0.4634 |
| 1.107 | 29.0 | 6380 | 1.2157 | 0.4634 |
| 1.098 | 30.0 | 6600 | 1.2113 | 0.4634 |
| 1.1034 | 31.0 | 6820 | 1.2071 | 0.4634 |
| 1.0941 | 32.0 | 7040 | 1.2031 | 0.4634 |
| 1.0839 | 33.0 | 7260 | 1.1993 | 0.4634 |
| 1.0528 | 34.0 | 7480 | 1.1956 | 0.4634 |
| 1.0292 | 35.0 | 7700 | 1.1922 | 0.4634 |
| 1.0585 | 36.0 | 7920 | 1.1890 | 0.4634 |
| 1.0434 | 37.0 | 8140 | 1.1859 | 0.4634 |
| 1.0597 | 38.0 | 8360 | 1.1831 | 0.4634 |
| 1.0626 | 39.0 | 8580 | 1.1805 | 0.4634 |
| 1.0375 | 40.0 | 8800 | 1.1782 | 0.4634 |
| 1.0422 | 41.0 | 9020 | 1.1761 | 0.4634 |
| 1.0304 | 42.0 | 9240 | 1.1742 | 0.4634 |
| 1.0373 | 43.0 | 9460 | 1.1726 | 0.4878 |
| 1.0134 | 44.0 | 9680 | 1.1712 | 0.4878 |
| 1.0323 | 45.0 | 9900 | 1.1701 | 0.4878 |
| 1.0327 | 46.0 | 10120 | 1.1692 | 0.5122 |
| 1.0599 | 47.0 | 10340 | 1.1685 | 0.5122 |
| 1.0079 | 48.0 | 10560 | 1.1681 | 0.5122 |
| 1.0145 | 49.0 | 10780 | 1.1679 | 0.5122 |
| 1.0358 | 50.0 | 11000 | 1.1678 | 0.5122 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2