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_0001_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: 0.7111111111111111
hushem_5x_deit_base_adamax_0001_fold1
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: 1.1576
- Accuracy: 0.7111
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 |
---|---|---|---|---|
1.238 | 1.0 | 27 | 1.3398 | 0.2667 |
0.9269 | 2.0 | 54 | 1.2685 | 0.4444 |
0.6591 | 3.0 | 81 | 1.1740 | 0.5333 |
0.5112 | 4.0 | 108 | 1.1289 | 0.5556 |
0.3169 | 5.0 | 135 | 1.0720 | 0.5778 |
0.2415 | 6.0 | 162 | 0.9458 | 0.6 |
0.1769 | 7.0 | 189 | 0.9250 | 0.6 |
0.0983 | 8.0 | 216 | 0.8893 | 0.6667 |
0.0567 | 9.0 | 243 | 0.8959 | 0.7111 |
0.0295 | 10.0 | 270 | 1.0130 | 0.5778 |
0.0202 | 11.0 | 297 | 0.9509 | 0.6889 |
0.0113 | 12.0 | 324 | 0.9586 | 0.7111 |
0.0094 | 13.0 | 351 | 0.9844 | 0.6889 |
0.0072 | 14.0 | 378 | 0.9965 | 0.7333 |
0.0063 | 15.0 | 405 | 1.0087 | 0.7111 |
0.005 | 16.0 | 432 | 1.0089 | 0.6889 |
0.0041 | 17.0 | 459 | 1.0347 | 0.6889 |
0.004 | 18.0 | 486 | 1.0569 | 0.6889 |
0.0034 | 19.0 | 513 | 1.0522 | 0.6889 |
0.0031 | 20.0 | 540 | 1.0681 | 0.6889 |
0.0027 | 21.0 | 567 | 1.0686 | 0.6889 |
0.0026 | 22.0 | 594 | 1.0745 | 0.6889 |
0.0023 | 23.0 | 621 | 1.0948 | 0.6889 |
0.0022 | 24.0 | 648 | 1.0979 | 0.6889 |
0.0021 | 25.0 | 675 | 1.0958 | 0.6889 |
0.0021 | 26.0 | 702 | 1.1008 | 0.6889 |
0.0018 | 27.0 | 729 | 1.1079 | 0.6889 |
0.0017 | 28.0 | 756 | 1.1114 | 0.6889 |
0.0019 | 29.0 | 783 | 1.1187 | 0.6889 |
0.0017 | 30.0 | 810 | 1.1246 | 0.6889 |
0.0016 | 31.0 | 837 | 1.1229 | 0.6889 |
0.0016 | 32.0 | 864 | 1.1290 | 0.6889 |
0.0014 | 33.0 | 891 | 1.1312 | 0.6889 |
0.0015 | 34.0 | 918 | 1.1349 | 0.6889 |
0.0014 | 35.0 | 945 | 1.1402 | 0.6889 |
0.0013 | 36.0 | 972 | 1.1442 | 0.6889 |
0.0013 | 37.0 | 999 | 1.1434 | 0.6889 |
0.0012 | 38.0 | 1026 | 1.1425 | 0.7111 |
0.0012 | 39.0 | 1053 | 1.1512 | 0.6889 |
0.0011 | 40.0 | 1080 | 1.1497 | 0.6889 |
0.0012 | 41.0 | 1107 | 1.1525 | 0.6889 |
0.0012 | 42.0 | 1134 | 1.1548 | 0.6889 |
0.0012 | 43.0 | 1161 | 1.1577 | 0.6889 |
0.0011 | 44.0 | 1188 | 1.1573 | 0.6889 |
0.0011 | 45.0 | 1215 | 1.1575 | 0.6889 |
0.0011 | 46.0 | 1242 | 1.1575 | 0.7111 |
0.0011 | 47.0 | 1269 | 1.1575 | 0.7111 |
0.0011 | 48.0 | 1296 | 1.1576 | 0.7111 |
0.0011 | 49.0 | 1323 | 1.1576 | 0.7111 |
0.0011 | 50.0 | 1350 | 1.1576 | 0.7111 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0