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_sgd_00001_fold5
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: 0.17073170731707318
hushem_5x_deit_base_sgd_00001_fold5
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: 1.3712
- Accuracy: 0.1707
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 |
|---|---|---|---|---|
| 1.4308 | 1.0 | 28 | 1.3745 | 0.2195 |
| 1.4381 | 2.0 | 56 | 1.3744 | 0.1951 |
| 1.4303 | 3.0 | 84 | 1.3742 | 0.1951 |
| 1.4196 | 4.0 | 112 | 1.3741 | 0.1951 |
| 1.4462 | 5.0 | 140 | 1.3739 | 0.1951 |
| 1.4289 | 6.0 | 168 | 1.3738 | 0.1951 |
| 1.4513 | 7.0 | 196 | 1.3737 | 0.1951 |
| 1.454 | 8.0 | 224 | 1.3736 | 0.1951 |
| 1.4395 | 9.0 | 252 | 1.3734 | 0.1951 |
| 1.4245 | 10.0 | 280 | 1.3733 | 0.1951 |
| 1.4477 | 11.0 | 308 | 1.3732 | 0.1951 |
| 1.4479 | 12.0 | 336 | 1.3731 | 0.1951 |
| 1.4264 | 13.0 | 364 | 1.3730 | 0.1951 |
| 1.4179 | 14.0 | 392 | 1.3729 | 0.1951 |
| 1.4497 | 15.0 | 420 | 1.3728 | 0.1951 |
| 1.4379 | 16.0 | 448 | 1.3727 | 0.1951 |
| 1.4414 | 17.0 | 476 | 1.3726 | 0.1951 |
| 1.452 | 18.0 | 504 | 1.3725 | 0.1951 |
| 1.4605 | 19.0 | 532 | 1.3724 | 0.1951 |
| 1.4508 | 20.0 | 560 | 1.3723 | 0.1951 |
| 1.4355 | 21.0 | 588 | 1.3722 | 0.1951 |
| 1.4232 | 22.0 | 616 | 1.3721 | 0.1951 |
| 1.4314 | 23.0 | 644 | 1.3721 | 0.1951 |
| 1.4464 | 24.0 | 672 | 1.3720 | 0.1951 |
| 1.4347 | 25.0 | 700 | 1.3719 | 0.1951 |
| 1.4331 | 26.0 | 728 | 1.3719 | 0.1707 |
| 1.4315 | 27.0 | 756 | 1.3718 | 0.1707 |
| 1.4463 | 28.0 | 784 | 1.3717 | 0.1707 |
| 1.4461 | 29.0 | 812 | 1.3717 | 0.1707 |
| 1.4576 | 30.0 | 840 | 1.3716 | 0.1707 |
| 1.4346 | 31.0 | 868 | 1.3716 | 0.1707 |
| 1.4439 | 32.0 | 896 | 1.3715 | 0.1707 |
| 1.4382 | 33.0 | 924 | 1.3715 | 0.1707 |
| 1.4458 | 34.0 | 952 | 1.3715 | 0.1707 |
| 1.4323 | 35.0 | 980 | 1.3714 | 0.1707 |
| 1.4333 | 36.0 | 1008 | 1.3714 | 0.1707 |
| 1.4238 | 37.0 | 1036 | 1.3714 | 0.1707 |
| 1.4188 | 38.0 | 1064 | 1.3713 | 0.1707 |
| 1.4355 | 39.0 | 1092 | 1.3713 | 0.1707 |
| 1.4499 | 40.0 | 1120 | 1.3713 | 0.1707 |
| 1.4289 | 41.0 | 1148 | 1.3713 | 0.1707 |
| 1.4376 | 42.0 | 1176 | 1.3712 | 0.1707 |
| 1.4427 | 43.0 | 1204 | 1.3712 | 0.1707 |
| 1.4421 | 44.0 | 1232 | 1.3712 | 0.1707 |
| 1.4536 | 45.0 | 1260 | 1.3712 | 0.1707 |
| 1.4126 | 46.0 | 1288 | 1.3712 | 0.1707 |
| 1.4355 | 47.0 | 1316 | 1.3712 | 0.1707 |
| 1.4384 | 48.0 | 1344 | 1.3712 | 0.1707 |
| 1.431 | 49.0 | 1372 | 1.3712 | 0.1707 |
| 1.4525 | 50.0 | 1400 | 1.3712 | 0.1707 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0