hushem_1x_deit_tiny_adamax_lr001_fold1
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: 1.5661
- Accuracy: 0.4444
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 | 2.2715 | 0.2667 |
| No log | 2.0 | 3 | 2.0269 | 0.4 |
| No log | 2.67 | 4 | 1.6111 | 0.2889 |
| No log | 4.0 | 6 | 1.4755 | 0.2444 |
| No log | 4.67 | 7 | 1.3818 | 0.4667 |
| No log | 6.0 | 9 | 1.3523 | 0.3111 |
| 1.6844 | 6.67 | 10 | 1.4010 | 0.2444 |
| 1.6844 | 8.0 | 12 | 1.2634 | 0.4444 |
| 1.6844 | 8.67 | 13 | 1.3983 | 0.4222 |
| 1.6844 | 10.0 | 15 | 1.7897 | 0.3778 |
| 1.6844 | 10.67 | 16 | 1.7305 | 0.3111 |
| 1.6844 | 12.0 | 18 | 1.3560 | 0.4667 |
| 1.6844 | 12.67 | 19 | 1.8545 | 0.4222 |
| 1.001 | 14.0 | 21 | 2.1000 | 0.3778 |
| 1.001 | 14.67 | 22 | 1.2257 | 0.4889 |
| 1.001 | 16.0 | 24 | 1.2741 | 0.4444 |
| 1.001 | 16.67 | 25 | 1.9098 | 0.3556 |
| 1.001 | 18.0 | 27 | 1.4981 | 0.3778 |
| 1.001 | 18.67 | 28 | 1.0949 | 0.4222 |
| 0.7366 | 20.0 | 30 | 1.1640 | 0.4222 |
| 0.7366 | 20.67 | 31 | 1.5156 | 0.3556 |
| 0.7366 | 22.0 | 33 | 1.8559 | 0.3556 |
| 0.7366 | 22.67 | 34 | 1.5735 | 0.4444 |
| 0.7366 | 24.0 | 36 | 1.3202 | 0.4222 |
| 0.7366 | 24.67 | 37 | 1.3837 | 0.4222 |
| 0.7366 | 26.0 | 39 | 1.6707 | 0.4 |
| 0.4908 | 26.67 | 40 | 1.8712 | 0.3778 |
| 0.4908 | 28.0 | 42 | 2.1885 | 0.3556 |
| 0.4908 | 28.67 | 43 | 2.0505 | 0.3556 |
| 0.4908 | 30.0 | 45 | 1.6855 | 0.4 |
| 0.4908 | 30.67 | 46 | 1.5304 | 0.4222 |
| 0.4908 | 32.0 | 48 | 1.5067 | 0.3778 |
| 0.4908 | 32.67 | 49 | 1.5442 | 0.4222 |
| 0.3287 | 33.33 | 50 | 1.5661 | 0.4444 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1