hushem_1x_deit_tiny_adamax_lr001_fold3
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: 1.6696
- Accuracy: 0.5814
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 | 4.2125 | 0.2558 |
| No log | 2.0 | 3 | 1.4682 | 0.2558 |
| No log | 2.67 | 4 | 1.6910 | 0.2558 |
| No log | 4.0 | 6 | 1.4476 | 0.2558 |
| No log | 4.67 | 7 | 1.3895 | 0.2558 |
| No log | 6.0 | 9 | 1.3751 | 0.2558 |
| 1.9073 | 6.67 | 10 | 1.3741 | 0.3953 |
| 1.9073 | 8.0 | 12 | 1.3957 | 0.3488 |
| 1.9073 | 8.67 | 13 | 1.3369 | 0.4419 |
| 1.9073 | 10.0 | 15 | 1.2847 | 0.4186 |
| 1.9073 | 10.67 | 16 | 1.3400 | 0.3953 |
| 1.9073 | 12.0 | 18 | 1.2676 | 0.3953 |
| 1.9073 | 12.67 | 19 | 1.2806 | 0.3721 |
| 1.1656 | 14.0 | 21 | 1.3652 | 0.3023 |
| 1.1656 | 14.67 | 22 | 1.3370 | 0.4419 |
| 1.1656 | 16.0 | 24 | 1.5165 | 0.3721 |
| 1.1656 | 16.67 | 25 | 1.5828 | 0.3953 |
| 1.1656 | 18.0 | 27 | 1.3210 | 0.3953 |
| 1.1656 | 18.67 | 28 | 1.3473 | 0.4419 |
| 0.9249 | 20.0 | 30 | 1.4346 | 0.4651 |
| 0.9249 | 20.67 | 31 | 1.3840 | 0.3953 |
| 0.9249 | 22.0 | 33 | 1.3578 | 0.4884 |
| 0.9249 | 22.67 | 34 | 1.3339 | 0.4884 |
| 0.9249 | 24.0 | 36 | 1.3509 | 0.4884 |
| 0.9249 | 24.67 | 37 | 1.3931 | 0.4884 |
| 0.9249 | 26.0 | 39 | 1.5691 | 0.5116 |
| 0.5495 | 26.67 | 40 | 1.5953 | 0.5349 |
| 0.5495 | 28.0 | 42 | 1.6688 | 0.5814 |
| 0.5495 | 28.67 | 43 | 1.6795 | 0.5581 |
| 0.5495 | 30.0 | 45 | 1.6839 | 0.5814 |
| 0.5495 | 30.67 | 46 | 1.6666 | 0.5814 |
| 0.5495 | 32.0 | 48 | 1.6555 | 0.5814 |
| 0.5495 | 32.67 | 49 | 1.6646 | 0.5814 |
| 0.2333 | 33.33 | 50 | 1.6696 | 0.5814 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1