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_adamax_001_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: 0.4222222222222222
hushem_5x_deit_tiny_adamax_001_fold1
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: 5.8123
- Accuracy: 0.4222
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 |
|---|---|---|---|---|
| 1.3956 | 1.0 | 27 | 1.9737 | 0.3111 |
| 0.888 | 2.0 | 54 | 1.5910 | 0.3556 |
| 1.1183 | 3.0 | 81 | 1.4091 | 0.3778 |
| 0.7709 | 4.0 | 108 | 1.4706 | 0.3778 |
| 0.9892 | 5.0 | 135 | 1.4916 | 0.4222 |
| 0.5847 | 6.0 | 162 | 2.0869 | 0.3778 |
| 0.6569 | 7.0 | 189 | 1.9470 | 0.3556 |
| 0.5263 | 8.0 | 216 | 1.6436 | 0.4 |
| 0.46 | 9.0 | 243 | 2.3342 | 0.3556 |
| 0.4825 | 10.0 | 270 | 1.8564 | 0.4222 |
| 0.3607 | 11.0 | 297 | 2.1004 | 0.4222 |
| 0.2444 | 12.0 | 324 | 2.4392 | 0.4222 |
| 0.3872 | 13.0 | 351 | 1.8032 | 0.4444 |
| 0.3209 | 14.0 | 378 | 2.9763 | 0.4 |
| 0.1884 | 15.0 | 405 | 2.8695 | 0.4667 |
| 0.1329 | 16.0 | 432 | 3.4787 | 0.4 |
| 0.2021 | 17.0 | 459 | 2.9858 | 0.4 |
| 0.1653 | 18.0 | 486 | 3.6825 | 0.4667 |
| 0.0813 | 19.0 | 513 | 3.2825 | 0.4444 |
| 0.1467 | 20.0 | 540 | 3.0809 | 0.4889 |
| 0.0538 | 21.0 | 567 | 3.9816 | 0.4222 |
| 0.1511 | 22.0 | 594 | 3.9404 | 0.4444 |
| 0.0505 | 23.0 | 621 | 4.4773 | 0.4667 |
| 0.0602 | 24.0 | 648 | 3.6484 | 0.4222 |
| 0.0403 | 25.0 | 675 | 4.0392 | 0.4444 |
| 0.005 | 26.0 | 702 | 3.8791 | 0.5556 |
| 0.0725 | 27.0 | 729 | 5.2091 | 0.4222 |
| 0.0084 | 28.0 | 756 | 4.7587 | 0.4222 |
| 0.0002 | 29.0 | 783 | 5.6091 | 0.3778 |
| 0.0001 | 30.0 | 810 | 5.5834 | 0.4222 |
| 0.0004 | 31.0 | 837 | 5.1075 | 0.4 |
| 0.0002 | 32.0 | 864 | 5.0938 | 0.4667 |
| 0.0014 | 33.0 | 891 | 5.4645 | 0.4667 |
| 0.0 | 34.0 | 918 | 5.9402 | 0.4222 |
| 0.0 | 35.0 | 945 | 5.8799 | 0.4222 |
| 0.0 | 36.0 | 972 | 5.8415 | 0.4222 |
| 0.0 | 37.0 | 999 | 5.8263 | 0.4222 |
| 0.0 | 38.0 | 1026 | 5.8129 | 0.4222 |
| 0.0 | 39.0 | 1053 | 5.8088 | 0.4222 |
| 0.0 | 40.0 | 1080 | 5.8085 | 0.4222 |
| 0.0 | 41.0 | 1107 | 5.8075 | 0.4222 |
| 0.0 | 42.0 | 1134 | 5.8084 | 0.4222 |
| 0.0 | 43.0 | 1161 | 5.8094 | 0.4222 |
| 0.0 | 44.0 | 1188 | 5.8109 | 0.4222 |
| 0.0 | 45.0 | 1215 | 5.8113 | 0.4222 |
| 0.0 | 46.0 | 1242 | 5.8120 | 0.4222 |
| 0.0 | 47.0 | 1269 | 5.8119 | 0.4222 |
| 0.0 | 48.0 | 1296 | 5.8123 | 0.4222 |
| 0.0 | 49.0 | 1323 | 5.8123 | 0.4222 |
| 0.0 | 50.0 | 1350 | 5.8123 | 0.4222 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0