hushem_1x_deit_tiny_adamax_lr001_fold4
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: 0.7197
- Accuracy: 0.7619
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
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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 |
|---|---|---|---|---|
| No log | 0.67 | 1 | 4.5038 | 0.2619 |
| No log | 2.0 | 3 | 1.5021 | 0.2381 |
| No log | 2.67 | 4 | 1.6655 | 0.2619 |
| No log | 4.0 | 6 | 1.3927 | 0.2381 |
| No log | 4.67 | 7 | 1.4664 | 0.2381 |
| No log | 6.0 | 9 | 1.4341 | 0.2381 |
| 1.9815 | 6.67 | 10 | 1.3866 | 0.5238 |
| 1.9815 | 8.0 | 12 | 1.4168 | 0.2381 |
| 1.9815 | 8.67 | 13 | 1.3770 | 0.2381 |
| 1.9815 | 10.0 | 15 | 1.3099 | 0.2619 |
| 1.9815 | 10.67 | 16 | 1.3229 | 0.2381 |
| 1.9815 | 12.0 | 18 | 1.2134 | 0.5 |
| 1.9815 | 12.67 | 19 | 1.1451 | 0.5238 |
| 1.3526 | 14.0 | 21 | 1.1341 | 0.6429 |
| 1.3526 | 14.67 | 22 | 0.9936 | 0.5952 |
| 1.3526 | 16.0 | 24 | 0.8768 | 0.6905 |
| 1.3526 | 16.67 | 25 | 0.9003 | 0.7143 |
| 1.3526 | 18.0 | 27 | 0.7438 | 0.7857 |
| 1.3526 | 18.67 | 28 | 0.6744 | 0.7143 |
| 1.0291 | 20.0 | 30 | 0.6946 | 0.7381 |
| 1.0291 | 20.67 | 31 | 0.6723 | 0.7381 |
| 1.0291 | 22.0 | 33 | 0.7030 | 0.7619 |
| 1.0291 | 22.67 | 34 | 0.6565 | 0.7857 |
| 1.0291 | 24.0 | 36 | 0.6394 | 0.7619 |
| 1.0291 | 24.67 | 37 | 0.7519 | 0.7143 |
| 1.0291 | 26.0 | 39 | 0.7489 | 0.6667 |
| 0.712 | 26.67 | 40 | 0.5267 | 0.8095 |
| 0.712 | 28.0 | 42 | 0.6166 | 0.7619 |
| 0.712 | 28.67 | 43 | 0.7873 | 0.7143 |
| 0.712 | 30.0 | 45 | 0.8388 | 0.7619 |
| 0.712 | 30.67 | 46 | 0.7831 | 0.7381 |
| 0.712 | 32.0 | 48 | 0.7151 | 0.7619 |
| 0.712 | 32.67 | 49 | 0.7126 | 0.7619 |
| 0.4557 | 33.33 | 50 | 0.7197 | 0.7619 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1