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_rms_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: 0.4888888888888889
hushem_5x_deit_base_rms_001_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: 1.9203
- 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 |
|---|---|---|---|---|
| 2.2898 | 1.0 | 27 | 1.4240 | 0.2444 |
| 1.4014 | 2.0 | 54 | 1.3895 | 0.1778 |
| 1.3975 | 3.0 | 81 | 1.3921 | 0.2444 |
| 1.3985 | 4.0 | 108 | 1.4006 | 0.2444 |
| 1.4125 | 5.0 | 135 | 1.3918 | 0.2667 |
| 1.3889 | 6.0 | 162 | 1.3878 | 0.2444 |
| 1.3949 | 7.0 | 189 | 1.3872 | 0.2667 |
| 1.4192 | 8.0 | 216 | 1.3990 | 0.2444 |
| 1.3939 | 9.0 | 243 | 1.3853 | 0.2889 |
| 1.3926 | 10.0 | 270 | 1.3626 | 0.4 |
| 1.356 | 11.0 | 297 | 1.2435 | 0.3778 |
| 1.2007 | 12.0 | 324 | 1.1323 | 0.3778 |
| 1.1878 | 13.0 | 351 | 1.2381 | 0.4 |
| 1.1084 | 14.0 | 378 | 1.4461 | 0.4222 |
| 1.0442 | 15.0 | 405 | 1.1938 | 0.4667 |
| 0.9336 | 16.0 | 432 | 1.2799 | 0.4 |
| 1.0799 | 17.0 | 459 | 1.1047 | 0.5333 |
| 0.9885 | 18.0 | 486 | 1.2688 | 0.4444 |
| 0.9753 | 19.0 | 513 | 1.2979 | 0.4444 |
| 0.9374 | 20.0 | 540 | 1.4547 | 0.4 |
| 0.8511 | 21.0 | 567 | 1.1517 | 0.4222 |
| 0.9007 | 22.0 | 594 | 1.4045 | 0.4444 |
| 0.8776 | 23.0 | 621 | 1.3447 | 0.4222 |
| 0.8333 | 24.0 | 648 | 1.2229 | 0.4889 |
| 0.8558 | 25.0 | 675 | 1.4746 | 0.4 |
| 0.8456 | 26.0 | 702 | 1.4066 | 0.4 |
| 0.8034 | 27.0 | 729 | 1.6488 | 0.3333 |
| 0.7686 | 28.0 | 756 | 1.4747 | 0.3778 |
| 0.7992 | 29.0 | 783 | 1.6794 | 0.4222 |
| 0.7462 | 30.0 | 810 | 1.9130 | 0.4 |
| 0.6946 | 31.0 | 837 | 1.5285 | 0.4 |
| 0.7435 | 32.0 | 864 | 1.6866 | 0.3556 |
| 0.6803 | 33.0 | 891 | 1.9290 | 0.3778 |
| 0.6227 | 34.0 | 918 | 1.4309 | 0.4222 |
| 0.6076 | 35.0 | 945 | 1.6567 | 0.4667 |
| 0.585 | 36.0 | 972 | 1.7272 | 0.3778 |
| 0.5538 | 37.0 | 999 | 1.6179 | 0.4 |
| 0.5528 | 38.0 | 1026 | 1.7890 | 0.3778 |
| 0.496 | 39.0 | 1053 | 1.6989 | 0.3556 |
| 0.4841 | 40.0 | 1080 | 1.8596 | 0.4 |
| 0.4712 | 41.0 | 1107 | 1.7704 | 0.4222 |
| 0.4626 | 42.0 | 1134 | 1.8917 | 0.4222 |
| 0.5151 | 43.0 | 1161 | 1.8143 | 0.4444 |
| 0.3695 | 44.0 | 1188 | 2.1532 | 0.3778 |
| 0.3767 | 45.0 | 1215 | 2.1009 | 0.4222 |
| 0.3138 | 46.0 | 1242 | 1.9441 | 0.4667 |
| 0.3279 | 47.0 | 1269 | 2.0701 | 0.4889 |
| 0.2542 | 48.0 | 1296 | 1.9192 | 0.4889 |
| 0.2778 | 49.0 | 1323 | 1.9203 | 0.4889 |
| 0.2872 | 50.0 | 1350 | 1.9203 | 0.4889 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0