metadata
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_3x_deit_small_sgd_00001_fold4
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: 0.505
smids_3x_deit_small_sgd_00001_fold4
This model is a fine-tuned version of facebook/deit-small-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.0105
- Accuracy: 0.505
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 |
|---|---|---|---|---|
| 1.0492 | 1.0 | 225 | 1.0666 | 0.43 |
| 1.0754 | 2.0 | 450 | 1.0640 | 0.43 |
| 1.0504 | 3.0 | 675 | 1.0616 | 0.4283 |
| 1.071 | 4.0 | 900 | 1.0591 | 0.43 |
| 1.052 | 5.0 | 1125 | 1.0568 | 0.4333 |
| 1.0616 | 6.0 | 1350 | 1.0545 | 0.44 |
| 1.0716 | 7.0 | 1575 | 1.0524 | 0.4433 |
| 1.0533 | 8.0 | 1800 | 1.0502 | 0.4417 |
| 1.0683 | 9.0 | 2025 | 1.0482 | 0.44 |
| 1.0375 | 10.0 | 2250 | 1.0461 | 0.4417 |
| 1.0594 | 11.0 | 2475 | 1.0442 | 0.445 |
| 1.0638 | 12.0 | 2700 | 1.0423 | 0.4467 |
| 1.0743 | 13.0 | 2925 | 1.0405 | 0.45 |
| 1.0117 | 14.0 | 3150 | 1.0387 | 0.4517 |
| 1.0604 | 15.0 | 3375 | 1.0370 | 0.4517 |
| 1.0498 | 16.0 | 3600 | 1.0354 | 0.4567 |
| 1.0315 | 17.0 | 3825 | 1.0338 | 0.46 |
| 1.0306 | 18.0 | 4050 | 1.0323 | 0.465 |
| 1.0262 | 19.0 | 4275 | 1.0309 | 0.4667 |
| 1.0262 | 20.0 | 4500 | 1.0294 | 0.4667 |
| 1.0341 | 21.0 | 4725 | 1.0281 | 0.4683 |
| 1.0464 | 22.0 | 4950 | 1.0268 | 0.4717 |
| 1.0098 | 23.0 | 5175 | 1.0255 | 0.4733 |
| 1.029 | 24.0 | 5400 | 1.0243 | 0.475 |
| 1.0091 | 25.0 | 5625 | 1.0231 | 0.4817 |
| 1.017 | 26.0 | 5850 | 1.0221 | 0.4833 |
| 1.0365 | 27.0 | 6075 | 1.0210 | 0.4883 |
| 1.019 | 28.0 | 6300 | 1.0200 | 0.4883 |
| 1.0442 | 29.0 | 6525 | 1.0191 | 0.4883 |
| 1.0415 | 30.0 | 6750 | 1.0182 | 0.4867 |
| 1.0316 | 31.0 | 6975 | 1.0174 | 0.4883 |
| 1.045 | 32.0 | 7200 | 1.0166 | 0.4883 |
| 1.0078 | 33.0 | 7425 | 1.0159 | 0.49 |
| 1.023 | 34.0 | 7650 | 1.0152 | 0.49 |
| 1.0174 | 35.0 | 7875 | 1.0146 | 0.495 |
| 1.0095 | 36.0 | 8100 | 1.0140 | 0.5 |
| 1.0162 | 37.0 | 8325 | 1.0135 | 0.5 |
| 1.0427 | 38.0 | 8550 | 1.0130 | 0.5 |
| 1.0155 | 39.0 | 8775 | 1.0125 | 0.5033 |
| 1.0159 | 40.0 | 9000 | 1.0122 | 0.505 |
| 1.0255 | 41.0 | 9225 | 1.0118 | 0.505 |
| 1.023 | 42.0 | 9450 | 1.0115 | 0.5067 |
| 1.0068 | 43.0 | 9675 | 1.0113 | 0.505 |
| 1.0321 | 44.0 | 9900 | 1.0110 | 0.505 |
| 1.0329 | 45.0 | 10125 | 1.0109 | 0.505 |
| 1.0275 | 46.0 | 10350 | 1.0107 | 0.505 |
| 1.0181 | 47.0 | 10575 | 1.0106 | 0.505 |
| 1.0137 | 48.0 | 10800 | 1.0106 | 0.505 |
| 1.0177 | 49.0 | 11025 | 1.0105 | 0.505 |
| 1.0148 | 50.0 | 11250 | 1.0105 | 0.505 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2