hushem_1x_deit_tiny_adamax_lr00001_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: 1.1208
- Accuracy: 0.5952
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
- 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 | 1.5521 | 0.1429 |
| No log | 2.0 | 3 | 1.4205 | 0.2857 |
| No log | 2.67 | 4 | 1.3862 | 0.3571 |
| No log | 4.0 | 6 | 1.3478 | 0.5238 |
| No log | 4.67 | 7 | 1.3332 | 0.5238 |
| No log | 6.0 | 9 | 1.3093 | 0.5238 |
| 1.4089 | 6.67 | 10 | 1.2970 | 0.5476 |
| 1.4089 | 8.0 | 12 | 1.2777 | 0.5714 |
| 1.4089 | 8.67 | 13 | 1.2689 | 0.5714 |
| 1.4089 | 10.0 | 15 | 1.2544 | 0.5714 |
| 1.4089 | 10.67 | 16 | 1.2478 | 0.5714 |
| 1.4089 | 12.0 | 18 | 1.2338 | 0.5714 |
| 1.4089 | 12.67 | 19 | 1.2267 | 0.5714 |
| 1.1506 | 14.0 | 21 | 1.2124 | 0.5714 |
| 1.1506 | 14.67 | 22 | 1.2049 | 0.5714 |
| 1.1506 | 16.0 | 24 | 1.1908 | 0.5714 |
| 1.1506 | 16.67 | 25 | 1.1843 | 0.5952 |
| 1.1506 | 18.0 | 27 | 1.1717 | 0.5952 |
| 1.1506 | 18.67 | 28 | 1.1659 | 0.5952 |
| 0.986 | 20.0 | 30 | 1.1576 | 0.5952 |
| 0.986 | 20.67 | 31 | 1.1537 | 0.5952 |
| 0.986 | 22.0 | 33 | 1.1470 | 0.5952 |
| 0.986 | 22.67 | 34 | 1.1439 | 0.5952 |
| 0.986 | 24.0 | 36 | 1.1385 | 0.5714 |
| 0.986 | 24.67 | 37 | 1.1362 | 0.5952 |
| 0.986 | 26.0 | 39 | 1.1320 | 0.5952 |
| 0.8708 | 26.67 | 40 | 1.1301 | 0.5952 |
| 0.8708 | 28.0 | 42 | 1.1268 | 0.5952 |
| 0.8708 | 28.67 | 43 | 1.1256 | 0.5952 |
| 0.8708 | 30.0 | 45 | 1.1234 | 0.5952 |
| 0.8708 | 30.67 | 46 | 1.1226 | 0.5952 |
| 0.8708 | 32.0 | 48 | 1.1214 | 0.5952 |
| 0.8708 | 32.67 | 49 | 1.1210 | 0.5952 |
| 0.8182 | 33.33 | 50 | 1.1208 | 0.5952 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1