hushem_1x_deit_tiny_adamax_lr00001_fold5
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: 1.2718
- Accuracy: 0.4634
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 | 1.6411 | 0.1220 |
| No log | 2.0 | 3 | 1.5318 | 0.1951 |
| No log | 2.67 | 4 | 1.5063 | 0.1707 |
| No log | 4.0 | 6 | 1.4764 | 0.3171 |
| No log | 4.67 | 7 | 1.4625 | 0.3171 |
| No log | 6.0 | 9 | 1.4352 | 0.3902 |
| 1.379 | 6.67 | 10 | 1.4210 | 0.4390 |
| 1.379 | 8.0 | 12 | 1.3993 | 0.4390 |
| 1.379 | 8.67 | 13 | 1.3906 | 0.4390 |
| 1.379 | 10.0 | 15 | 1.3747 | 0.4146 |
| 1.379 | 10.67 | 16 | 1.3676 | 0.4146 |
| 1.379 | 12.0 | 18 | 1.3554 | 0.4146 |
| 1.379 | 12.67 | 19 | 1.3500 | 0.4146 |
| 1.107 | 14.0 | 21 | 1.3389 | 0.4146 |
| 1.107 | 14.67 | 22 | 1.3348 | 0.4146 |
| 1.107 | 16.0 | 24 | 1.3265 | 0.4390 |
| 1.107 | 16.67 | 25 | 1.3236 | 0.4634 |
| 1.107 | 18.0 | 27 | 1.3162 | 0.4634 |
| 1.107 | 18.67 | 28 | 1.3129 | 0.4390 |
| 0.9495 | 20.0 | 30 | 1.3051 | 0.4390 |
| 0.9495 | 20.67 | 31 | 1.3019 | 0.4390 |
| 0.9495 | 22.0 | 33 | 1.2961 | 0.4390 |
| 0.9495 | 22.67 | 34 | 1.2934 | 0.4634 |
| 0.9495 | 24.0 | 36 | 1.2879 | 0.4390 |
| 0.9495 | 24.67 | 37 | 1.2851 | 0.4390 |
| 0.9495 | 26.0 | 39 | 1.2815 | 0.4390 |
| 0.8401 | 26.67 | 40 | 1.2802 | 0.4390 |
| 0.8401 | 28.0 | 42 | 1.2775 | 0.4390 |
| 0.8401 | 28.67 | 43 | 1.2761 | 0.4390 |
| 0.8401 | 30.0 | 45 | 1.2740 | 0.4390 |
| 0.8401 | 30.67 | 46 | 1.2734 | 0.4390 |
| 0.8401 | 32.0 | 48 | 1.2723 | 0.4634 |
| 0.8401 | 32.67 | 49 | 1.2719 | 0.4634 |
| 0.7816 | 33.33 | 50 | 1.2718 | 0.4634 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1