metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_base_adamax_001_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: 0.6904761904761905
hushem_5x_deit_base_adamax_001_fold4
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: 1.8006
- Accuracy: 0.6905
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 |
|---|---|---|---|---|
| 1.4494 | 1.0 | 28 | 1.3719 | 0.2619 |
| 1.2522 | 2.0 | 56 | 0.9742 | 0.6667 |
| 1.0638 | 3.0 | 84 | 0.9282 | 0.4286 |
| 0.9326 | 4.0 | 112 | 0.9751 | 0.7381 |
| 0.9775 | 5.0 | 140 | 0.6128 | 0.8333 |
| 0.8386 | 6.0 | 168 | 0.6453 | 0.6905 |
| 0.7523 | 7.0 | 196 | 0.8760 | 0.5952 |
| 0.8483 | 8.0 | 224 | 0.6776 | 0.6905 |
| 0.7007 | 9.0 | 252 | 0.6406 | 0.7381 |
| 0.6736 | 10.0 | 280 | 1.1732 | 0.5714 |
| 0.6667 | 11.0 | 308 | 0.8999 | 0.7143 |
| 0.5535 | 12.0 | 336 | 0.7518 | 0.7143 |
| 0.5519 | 13.0 | 364 | 1.2198 | 0.6429 |
| 0.4746 | 14.0 | 392 | 1.2629 | 0.6190 |
| 0.4049 | 15.0 | 420 | 1.0670 | 0.7143 |
| 0.2485 | 16.0 | 448 | 1.3207 | 0.6667 |
| 0.2835 | 17.0 | 476 | 0.9080 | 0.7143 |
| 0.1908 | 18.0 | 504 | 0.9684 | 0.6905 |
| 0.1239 | 19.0 | 532 | 0.8600 | 0.8333 |
| 0.2177 | 20.0 | 560 | 1.2908 | 0.6667 |
| 0.0633 | 21.0 | 588 | 1.7014 | 0.7143 |
| 0.0847 | 22.0 | 616 | 1.3740 | 0.7857 |
| 0.1199 | 23.0 | 644 | 1.1620 | 0.8095 |
| 0.0618 | 24.0 | 672 | 1.7626 | 0.7857 |
| 0.0552 | 25.0 | 700 | 1.7596 | 0.7381 |
| 0.0166 | 26.0 | 728 | 1.4380 | 0.7143 |
| 0.0048 | 27.0 | 756 | 2.1450 | 0.6667 |
| 0.0064 | 28.0 | 784 | 1.7983 | 0.7381 |
| 0.0065 | 29.0 | 812 | 1.9453 | 0.6429 |
| 0.0052 | 30.0 | 840 | 1.5896 | 0.7619 |
| 0.0125 | 31.0 | 868 | 1.6540 | 0.7381 |
| 0.0008 | 32.0 | 896 | 1.7879 | 0.7619 |
| 0.0001 | 33.0 | 924 | 1.9506 | 0.7381 |
| 0.0002 | 34.0 | 952 | 1.7166 | 0.7143 |
| 0.0 | 35.0 | 980 | 1.7316 | 0.6905 |
| 0.0 | 36.0 | 1008 | 1.7446 | 0.6905 |
| 0.0 | 37.0 | 1036 | 1.7559 | 0.6905 |
| 0.0 | 38.0 | 1064 | 1.7638 | 0.6905 |
| 0.0 | 39.0 | 1092 | 1.7724 | 0.6905 |
| 0.0 | 40.0 | 1120 | 1.7784 | 0.6905 |
| 0.0 | 41.0 | 1148 | 1.7832 | 0.6905 |
| 0.0 | 42.0 | 1176 | 1.7877 | 0.6905 |
| 0.0 | 43.0 | 1204 | 1.7918 | 0.6905 |
| 0.0 | 44.0 | 1232 | 1.7950 | 0.6905 |
| 0.0 | 45.0 | 1260 | 1.7970 | 0.6905 |
| 0.0 | 46.0 | 1288 | 1.7988 | 0.6905 |
| 0.0 | 47.0 | 1316 | 1.8001 | 0.6905 |
| 0.0 | 48.0 | 1344 | 1.8006 | 0.6905 |
| 0.0 | 49.0 | 1372 | 1.8006 | 0.6905 |
| 0.0 | 50.0 | 1400 | 1.8006 | 0.6905 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0