deit-base-distilled-patch16-224-hasta-85-fold3
This model is a fine-tuned version of facebook/deit-base-distilled-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.7871
- Accuracy: 0.7273
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: 5e-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: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 0.8686 | 0.6364 |
| No log | 2.0 | 2 | 0.7871 | 0.7273 |
| No log | 3.0 | 3 | 0.7116 | 0.7273 |
| No log | 4.0 | 4 | 0.7585 | 0.7273 |
| No log | 5.0 | 5 | 0.9216 | 0.7273 |
| No log | 6.0 | 6 | 1.0848 | 0.7273 |
| No log | 7.0 | 7 | 1.1931 | 0.7273 |
| No log | 8.0 | 8 | 1.2543 | 0.7273 |
| No log | 9.0 | 9 | 1.3098 | 0.7273 |
| 0.2667 | 10.0 | 10 | 1.3979 | 0.7273 |
| 0.2667 | 11.0 | 11 | 1.4209 | 0.7273 |
| 0.2667 | 12.0 | 12 | 1.4302 | 0.7273 |
| 0.2667 | 13.0 | 13 | 1.4202 | 0.7273 |
| 0.2667 | 14.0 | 14 | 1.3569 | 0.7273 |
| 0.2667 | 15.0 | 15 | 1.3033 | 0.7273 |
| 0.2667 | 16.0 | 16 | 1.3414 | 0.7273 |
| 0.2667 | 17.0 | 17 | 1.4312 | 0.7273 |
| 0.2667 | 18.0 | 18 | 1.6063 | 0.7273 |
| 0.2667 | 19.0 | 19 | 1.7308 | 0.7273 |
| 0.1296 | 20.0 | 20 | 1.7541 | 0.7273 |
| 0.1296 | 21.0 | 21 | 1.7183 | 0.7273 |
| 0.1296 | 22.0 | 22 | 1.6395 | 0.7273 |
| 0.1296 | 23.0 | 23 | 1.6197 | 0.7273 |
| 0.1296 | 24.0 | 24 | 1.6525 | 0.7273 |
| 0.1296 | 25.0 | 25 | 1.7183 | 0.7273 |
| 0.1296 | 26.0 | 26 | 1.7120 | 0.7273 |
| 0.1296 | 27.0 | 27 | 1.6748 | 0.7273 |
| 0.1296 | 28.0 | 28 | 1.5840 | 0.7273 |
| 0.1296 | 29.0 | 29 | 1.5963 | 0.7273 |
| 0.0834 | 30.0 | 30 | 1.7016 | 0.7273 |
| 0.0834 | 31.0 | 31 | 1.7780 | 0.7273 |
| 0.0834 | 32.0 | 32 | 1.7943 | 0.7273 |
| 0.0834 | 33.0 | 33 | 1.7993 | 0.7273 |
| 0.0834 | 34.0 | 34 | 1.7873 | 0.7273 |
| 0.0834 | 35.0 | 35 | 1.8196 | 0.7273 |
| 0.0834 | 36.0 | 36 | 1.9190 | 0.7273 |
| 0.0834 | 37.0 | 37 | 2.0467 | 0.7273 |
| 0.0834 | 38.0 | 38 | 2.1647 | 0.7273 |
| 0.0834 | 39.0 | 39 | 2.2634 | 0.7273 |
| 0.0441 | 40.0 | 40 | 2.3170 | 0.7273 |
| 0.0441 | 41.0 | 41 | 2.3263 | 0.7273 |
| 0.0441 | 42.0 | 42 | 2.2991 | 0.7273 |
| 0.0441 | 43.0 | 43 | 2.2792 | 0.7273 |
| 0.0441 | 44.0 | 44 | 2.2572 | 0.7273 |
| 0.0441 | 45.0 | 45 | 2.2751 | 0.7273 |
| 0.0441 | 46.0 | 46 | 2.3103 | 0.7273 |
| 0.0441 | 47.0 | 47 | 2.3325 | 0.7273 |
| 0.0441 | 48.0 | 48 | 2.3259 | 0.7273 |
| 0.0441 | 49.0 | 49 | 2.2974 | 0.7273 |
| 0.0437 | 50.0 | 50 | 2.2312 | 0.7273 |
| 0.0437 | 51.0 | 51 | 2.1638 | 0.7273 |
| 0.0437 | 52.0 | 52 | 2.0963 | 0.7273 |
| 0.0437 | 53.0 | 53 | 2.0074 | 0.7273 |
| 0.0437 | 54.0 | 54 | 1.9069 | 0.7273 |
| 0.0437 | 55.0 | 55 | 1.8899 | 0.7273 |
| 0.0437 | 56.0 | 56 | 1.9432 | 0.7273 |
| 0.0437 | 57.0 | 57 | 2.0307 | 0.7273 |
| 0.0437 | 58.0 | 58 | 2.1621 | 0.7273 |
| 0.0437 | 59.0 | 59 | 2.2470 | 0.7273 |
| 0.04 | 60.0 | 60 | 2.3281 | 0.7273 |
| 0.04 | 61.0 | 61 | 2.3529 | 0.7273 |
| 0.04 | 62.0 | 62 | 2.3491 | 0.7273 |
| 0.04 | 63.0 | 63 | 2.3534 | 0.7273 |
| 0.04 | 64.0 | 64 | 2.3541 | 0.7273 |
| 0.04 | 65.0 | 65 | 2.3474 | 0.7273 |
| 0.04 | 66.0 | 66 | 2.3363 | 0.7273 |
| 0.04 | 67.0 | 67 | 2.3193 | 0.7273 |
| 0.04 | 68.0 | 68 | 2.3144 | 0.7273 |
| 0.04 | 69.0 | 69 | 2.2847 | 0.7273 |
| 0.0232 | 70.0 | 70 | 2.2488 | 0.7273 |
| 0.0232 | 71.0 | 71 | 2.2175 | 0.7273 |
| 0.0232 | 72.0 | 72 | 2.1898 | 0.7273 |
| 0.0232 | 73.0 | 73 | 2.1797 | 0.7273 |
| 0.0232 | 74.0 | 74 | 2.1829 | 0.7273 |
| 0.0232 | 75.0 | 75 | 2.1806 | 0.7273 |
| 0.0232 | 76.0 | 76 | 2.1685 | 0.7273 |
| 0.0232 | 77.0 | 77 | 2.1505 | 0.7273 |
| 0.0232 | 78.0 | 78 | 2.1548 | 0.7273 |
| 0.0232 | 79.0 | 79 | 2.1650 | 0.7273 |
| 0.0243 | 80.0 | 80 | 2.1961 | 0.7273 |
| 0.0243 | 81.0 | 81 | 2.2283 | 0.7273 |
| 0.0243 | 82.0 | 82 | 2.2619 | 0.7273 |
| 0.0243 | 83.0 | 83 | 2.2783 | 0.7273 |
| 0.0243 | 84.0 | 84 | 2.2796 | 0.7273 |
| 0.0243 | 85.0 | 85 | 2.2780 | 0.7273 |
| 0.0243 | 86.0 | 86 | 2.2769 | 0.7273 |
| 0.0243 | 87.0 | 87 | 2.2655 | 0.7273 |
| 0.0243 | 88.0 | 88 | 2.2584 | 0.7273 |
| 0.0243 | 89.0 | 89 | 2.2419 | 0.7273 |
| 0.0301 | 90.0 | 90 | 2.2299 | 0.7273 |
| 0.0301 | 91.0 | 91 | 2.2151 | 0.7273 |
| 0.0301 | 92.0 | 92 | 2.2038 | 0.7273 |
| 0.0301 | 93.0 | 93 | 2.1956 | 0.7273 |
| 0.0301 | 94.0 | 94 | 2.1946 | 0.7273 |
| 0.0301 | 95.0 | 95 | 2.2012 | 0.7273 |
| 0.0301 | 96.0 | 96 | 2.2079 | 0.7273 |
| 0.0301 | 97.0 | 97 | 2.2151 | 0.7273 |
| 0.0301 | 98.0 | 98 | 2.2219 | 0.7273 |
| 0.0301 | 99.0 | 99 | 2.2261 | 0.7273 |
| 0.0154 | 100.0 | 100 | 2.2286 | 0.7273 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1