metadata
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_5x_deit_tiny_rms_0001_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: 0.8571428571428571
hushem_5x_deit_tiny_rms_0001_fold4
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: 1.1423
- Accuracy: 0.8571
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 |
|---|---|---|---|---|
| 1.5018 | 1.0 | 28 | 1.4435 | 0.2381 |
| 1.3915 | 2.0 | 56 | 1.7481 | 0.2619 |
| 0.9807 | 3.0 | 84 | 1.0427 | 0.5 |
| 0.6115 | 4.0 | 112 | 0.6071 | 0.6905 |
| 0.3048 | 5.0 | 140 | 0.8476 | 0.8095 |
| 0.2247 | 6.0 | 168 | 1.1744 | 0.7143 |
| 0.1107 | 7.0 | 196 | 0.4922 | 0.8810 |
| 0.0936 | 8.0 | 224 | 0.8411 | 0.8333 |
| 0.052 | 9.0 | 252 | 1.2457 | 0.7381 |
| 0.1043 | 10.0 | 280 | 0.5514 | 0.8810 |
| 0.0015 | 11.0 | 308 | 0.9844 | 0.8333 |
| 0.0204 | 12.0 | 336 | 0.4946 | 0.8333 |
| 0.0149 | 13.0 | 364 | 0.8042 | 0.8571 |
| 0.0016 | 14.0 | 392 | 1.2413 | 0.7857 |
| 0.0114 | 15.0 | 420 | 1.0274 | 0.8333 |
| 0.0352 | 16.0 | 448 | 0.9012 | 0.8095 |
| 0.0613 | 17.0 | 476 | 1.0834 | 0.7857 |
| 0.0277 | 18.0 | 504 | 0.9416 | 0.8571 |
| 0.0099 | 19.0 | 532 | 1.2649 | 0.7857 |
| 0.0251 | 20.0 | 560 | 0.9863 | 0.8571 |
| 0.0001 | 21.0 | 588 | 0.9424 | 0.8333 |
| 0.0001 | 22.0 | 616 | 0.9653 | 0.8571 |
| 0.0 | 23.0 | 644 | 0.9755 | 0.8571 |
| 0.0 | 24.0 | 672 | 0.9859 | 0.8571 |
| 0.0 | 25.0 | 700 | 0.9939 | 0.8571 |
| 0.0 | 26.0 | 728 | 1.0026 | 0.8571 |
| 0.0 | 27.0 | 756 | 1.0107 | 0.8571 |
| 0.0 | 28.0 | 784 | 1.0180 | 0.8571 |
| 0.0 | 29.0 | 812 | 1.0261 | 0.8571 |
| 0.0 | 30.0 | 840 | 1.0335 | 0.8571 |
| 0.0 | 31.0 | 868 | 1.0404 | 0.8571 |
| 0.0 | 32.0 | 896 | 1.0484 | 0.8571 |
| 0.0 | 33.0 | 924 | 1.0559 | 0.8571 |
| 0.0 | 34.0 | 952 | 1.0642 | 0.8571 |
| 0.0 | 35.0 | 980 | 1.0715 | 0.8571 |
| 0.0 | 36.0 | 1008 | 1.0789 | 0.8571 |
| 0.0 | 37.0 | 1036 | 1.0861 | 0.8571 |
| 0.0 | 38.0 | 1064 | 1.0922 | 0.8571 |
| 0.0 | 39.0 | 1092 | 1.0992 | 0.8571 |
| 0.0 | 40.0 | 1120 | 1.1058 | 0.8571 |
| 0.0 | 41.0 | 1148 | 1.1124 | 0.8571 |
| 0.0 | 42.0 | 1176 | 1.1189 | 0.8571 |
| 0.0 | 43.0 | 1204 | 1.1246 | 0.8571 |
| 0.0 | 44.0 | 1232 | 1.1302 | 0.8571 |
| 0.0 | 45.0 | 1260 | 1.1347 | 0.8571 |
| 0.0 | 46.0 | 1288 | 1.1383 | 0.8571 |
| 0.0 | 47.0 | 1316 | 1.1409 | 0.8571 |
| 0.0 | 48.0 | 1344 | 1.1422 | 0.8571 |
| 0.0 | 49.0 | 1372 | 1.1423 | 0.8571 |
| 0.0 | 50.0 | 1400 | 1.1423 | 0.8571 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0