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_fold2
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: 0.4888888888888889
hushem_5x_deit_base_adamax_001_fold2
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: 5.7416
- Accuracy: 0.4889
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 |
|---|---|---|---|---|
| 1.4053 | 1.0 | 27 | 1.3685 | 0.3111 |
| 1.3925 | 2.0 | 54 | 3.6868 | 0.2889 |
| 1.2318 | 3.0 | 81 | 1.5265 | 0.3333 |
| 1.1218 | 4.0 | 108 | 1.3720 | 0.3778 |
| 0.9389 | 5.0 | 135 | 1.3538 | 0.4444 |
| 0.8792 | 6.0 | 162 | 1.1885 | 0.4444 |
| 0.8387 | 7.0 | 189 | 1.3407 | 0.4889 |
| 0.7915 | 8.0 | 216 | 1.2361 | 0.4222 |
| 0.79 | 9.0 | 243 | 1.2485 | 0.4667 |
| 0.7076 | 10.0 | 270 | 1.6183 | 0.5333 |
| 0.6051 | 11.0 | 297 | 1.7700 | 0.4889 |
| 0.5603 | 12.0 | 324 | 1.7918 | 0.3556 |
| 0.6144 | 13.0 | 351 | 2.1767 | 0.5556 |
| 0.5279 | 14.0 | 378 | 1.6851 | 0.3778 |
| 0.3562 | 15.0 | 405 | 2.1689 | 0.4444 |
| 0.3897 | 16.0 | 432 | 2.2755 | 0.4667 |
| 0.4523 | 17.0 | 459 | 2.3235 | 0.4222 |
| 0.5055 | 18.0 | 486 | 2.6282 | 0.5556 |
| 0.2707 | 19.0 | 513 | 2.3398 | 0.5333 |
| 0.4827 | 20.0 | 540 | 2.5025 | 0.5111 |
| 0.2449 | 21.0 | 567 | 2.2455 | 0.4667 |
| 0.3199 | 22.0 | 594 | 3.8583 | 0.5333 |
| 0.2715 | 23.0 | 621 | 2.9016 | 0.5556 |
| 0.2241 | 24.0 | 648 | 2.9266 | 0.4444 |
| 0.1264 | 25.0 | 675 | 3.0321 | 0.4222 |
| 0.1028 | 26.0 | 702 | 3.8439 | 0.5778 |
| 0.2082 | 27.0 | 729 | 3.7749 | 0.5333 |
| 0.2344 | 28.0 | 756 | 3.4616 | 0.5333 |
| 0.0842 | 29.0 | 783 | 3.5970 | 0.5111 |
| 0.0483 | 30.0 | 810 | 4.3955 | 0.5111 |
| 0.1454 | 31.0 | 837 | 3.9120 | 0.5556 |
| 0.0972 | 32.0 | 864 | 3.9463 | 0.4889 |
| 0.014 | 33.0 | 891 | 4.4955 | 0.4889 |
| 0.0007 | 34.0 | 918 | 5.1958 | 0.5111 |
| 0.0273 | 35.0 | 945 | 5.0022 | 0.4889 |
| 0.0071 | 36.0 | 972 | 4.9340 | 0.5333 |
| 0.0003 | 37.0 | 999 | 5.2310 | 0.4889 |
| 0.0004 | 38.0 | 1026 | 5.5820 | 0.4889 |
| 0.0001 | 39.0 | 1053 | 5.6491 | 0.4889 |
| 0.0001 | 40.0 | 1080 | 5.6867 | 0.4889 |
| 0.0001 | 41.0 | 1107 | 5.7009 | 0.4889 |
| 0.0001 | 42.0 | 1134 | 5.7115 | 0.4889 |
| 0.0 | 43.0 | 1161 | 5.7213 | 0.4889 |
| 0.0001 | 44.0 | 1188 | 5.7289 | 0.4889 |
| 0.0001 | 45.0 | 1215 | 5.7342 | 0.4889 |
| 0.0 | 46.0 | 1242 | 5.7384 | 0.4889 |
| 0.0 | 47.0 | 1269 | 5.7406 | 0.4889 |
| 0.0 | 48.0 | 1296 | 5.7416 | 0.4889 |
| 0.0001 | 49.0 | 1323 | 5.7416 | 0.4889 |
| 0.0 | 50.0 | 1350 | 5.7416 | 0.4889 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0