hushem_1x_deit_tiny_adamax_lr00001_fold2
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: 1.4306
- Accuracy: 0.2889
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 | 1.6419 | 0.1111 |
| No log | 2.0 | 3 | 1.5215 | 0.1556 |
| No log | 2.67 | 4 | 1.5000 | 0.1778 |
| No log | 4.0 | 6 | 1.4887 | 0.2444 |
| No log | 4.67 | 7 | 1.4849 | 0.2222 |
| No log | 6.0 | 9 | 1.4754 | 0.2444 |
| 1.3642 | 6.67 | 10 | 1.4684 | 0.2667 |
| 1.3642 | 8.0 | 12 | 1.4571 | 0.2667 |
| 1.3642 | 8.67 | 13 | 1.4523 | 0.2667 |
| 1.3642 | 10.0 | 15 | 1.4422 | 0.2667 |
| 1.3642 | 10.67 | 16 | 1.4392 | 0.2444 |
| 1.3642 | 12.0 | 18 | 1.4341 | 0.2444 |
| 1.3642 | 12.67 | 19 | 1.4327 | 0.2444 |
| 1.1012 | 14.0 | 21 | 1.4319 | 0.2667 |
| 1.1012 | 14.67 | 22 | 1.4329 | 0.2667 |
| 1.1012 | 16.0 | 24 | 1.4330 | 0.2889 |
| 1.1012 | 16.67 | 25 | 1.4333 | 0.2889 |
| 1.1012 | 18.0 | 27 | 1.4342 | 0.2889 |
| 1.1012 | 18.67 | 28 | 1.4339 | 0.2889 |
| 0.9232 | 20.0 | 30 | 1.4351 | 0.2889 |
| 0.9232 | 20.67 | 31 | 1.4354 | 0.2889 |
| 0.9232 | 22.0 | 33 | 1.4352 | 0.2889 |
| 0.9232 | 22.67 | 34 | 1.4353 | 0.2889 |
| 0.9232 | 24.0 | 36 | 1.4349 | 0.2889 |
| 0.9232 | 24.67 | 37 | 1.4347 | 0.2889 |
| 0.9232 | 26.0 | 39 | 1.4341 | 0.2889 |
| 0.8235 | 26.67 | 40 | 1.4334 | 0.2889 |
| 0.8235 | 28.0 | 42 | 1.4325 | 0.2889 |
| 0.8235 | 28.67 | 43 | 1.4325 | 0.2889 |
| 0.8235 | 30.0 | 45 | 1.4317 | 0.2889 |
| 0.8235 | 30.67 | 46 | 1.4312 | 0.2889 |
| 0.8235 | 32.0 | 48 | 1.4307 | 0.2889 |
| 0.8235 | 32.67 | 49 | 1.4307 | 0.2889 |
| 0.7752 | 33.33 | 50 | 1.4306 | 0.2889 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1