hushem_1x_deit_tiny_adamax_lr0001_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: 0.8641
- Accuracy: 0.6977
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: 0.0001
- 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 | 1.6041 | 0.2558 |
| No log | 2.0 | 3 | 1.2890 | 0.3953 |
| No log | 2.67 | 4 | 1.2944 | 0.3023 |
| No log | 4.0 | 6 | 1.2013 | 0.4186 |
| No log | 4.67 | 7 | 1.1135 | 0.4186 |
| No log | 6.0 | 9 | 1.0796 | 0.5349 |
| 1.2559 | 6.67 | 10 | 1.0570 | 0.5581 |
| 1.2559 | 8.0 | 12 | 1.1038 | 0.4884 |
| 1.2559 | 8.67 | 13 | 1.0764 | 0.4884 |
| 1.2559 | 10.0 | 15 | 0.9749 | 0.5349 |
| 1.2559 | 10.67 | 16 | 0.9354 | 0.5581 |
| 1.2559 | 12.0 | 18 | 0.9274 | 0.6279 |
| 1.2559 | 12.67 | 19 | 0.9435 | 0.6512 |
| 0.4315 | 14.0 | 21 | 0.9225 | 0.6512 |
| 0.4315 | 14.67 | 22 | 0.9168 | 0.6279 |
| 0.4315 | 16.0 | 24 | 0.8830 | 0.6279 |
| 0.4315 | 16.67 | 25 | 0.8956 | 0.6512 |
| 0.4315 | 18.0 | 27 | 0.9038 | 0.6744 |
| 0.4315 | 18.67 | 28 | 0.8913 | 0.6744 |
| 0.058 | 20.0 | 30 | 0.8683 | 0.6512 |
| 0.058 | 20.67 | 31 | 0.8553 | 0.6744 |
| 0.058 | 22.0 | 33 | 0.8508 | 0.6977 |
| 0.058 | 22.67 | 34 | 0.8546 | 0.6977 |
| 0.058 | 24.0 | 36 | 0.8627 | 0.6977 |
| 0.058 | 24.67 | 37 | 0.8639 | 0.6977 |
| 0.058 | 26.0 | 39 | 0.8636 | 0.7209 |
| 0.0086 | 26.67 | 40 | 0.8627 | 0.7209 |
| 0.0086 | 28.0 | 42 | 0.8622 | 0.7209 |
| 0.0086 | 28.67 | 43 | 0.8622 | 0.6977 |
| 0.0086 | 30.0 | 45 | 0.8629 | 0.6977 |
| 0.0086 | 30.67 | 46 | 0.8632 | 0.6977 |
| 0.0086 | 32.0 | 48 | 0.8638 | 0.6977 |
| 0.0086 | 32.67 | 49 | 0.8640 | 0.6977 |
| 0.004 | 33.33 | 50 | 0.8641 | 0.6977 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1