deit-base-distilled-patch16-224-hasta-85-fold2
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: 1.0159
- 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 | 1.3509 | 0.1818 |
| No log | 2.0 | 2 | 1.2094 | 0.1818 |
| No log | 3.0 | 3 | 1.0159 | 0.7273 |
| No log | 4.0 | 4 | 0.9047 | 0.6364 |
| No log | 5.0 | 5 | 0.9481 | 0.7273 |
| No log | 6.0 | 6 | 1.1337 | 0.7273 |
| No log | 7.0 | 7 | 1.2464 | 0.7273 |
| No log | 8.0 | 8 | 1.2335 | 0.7273 |
| No log | 9.0 | 9 | 1.1432 | 0.7273 |
| 0.4248 | 10.0 | 10 | 1.0979 | 0.7273 |
| 0.4248 | 11.0 | 11 | 1.1069 | 0.7273 |
| 0.4248 | 12.0 | 12 | 1.1633 | 0.7273 |
| 0.4248 | 13.0 | 13 | 1.1650 | 0.7273 |
| 0.4248 | 14.0 | 14 | 1.1332 | 0.7273 |
| 0.4248 | 15.0 | 15 | 1.1423 | 0.7273 |
| 0.4248 | 16.0 | 16 | 1.1208 | 0.7273 |
| 0.4248 | 17.0 | 17 | 1.0566 | 0.7273 |
| 0.4248 | 18.0 | 18 | 1.0348 | 0.7273 |
| 0.4248 | 19.0 | 19 | 1.0146 | 0.7273 |
| 0.1813 | 20.0 | 20 | 1.0062 | 0.7273 |
| 0.1813 | 21.0 | 21 | 1.0748 | 0.7273 |
| 0.1813 | 22.0 | 22 | 1.1673 | 0.7273 |
| 0.1813 | 23.0 | 23 | 1.2477 | 0.7273 |
| 0.1813 | 24.0 | 24 | 1.2457 | 0.7273 |
| 0.1813 | 25.0 | 25 | 1.1424 | 0.7273 |
| 0.1813 | 26.0 | 26 | 1.0439 | 0.7273 |
| 0.1813 | 27.0 | 27 | 0.9436 | 0.7273 |
| 0.1813 | 28.0 | 28 | 0.8254 | 0.7273 |
| 0.1813 | 29.0 | 29 | 0.7963 | 0.7273 |
| 0.1021 | 30.0 | 30 | 0.8055 | 0.7273 |
| 0.1021 | 31.0 | 31 | 0.7734 | 0.7273 |
| 0.1021 | 32.0 | 32 | 0.7069 | 0.7273 |
| 0.1021 | 33.0 | 33 | 0.7235 | 0.7273 |
| 0.1021 | 34.0 | 34 | 0.8200 | 0.7273 |
| 0.1021 | 35.0 | 35 | 0.8484 | 0.7273 |
| 0.1021 | 36.0 | 36 | 0.9380 | 0.7273 |
| 0.1021 | 37.0 | 37 | 1.0584 | 0.7273 |
| 0.1021 | 38.0 | 38 | 1.1803 | 0.7273 |
| 0.1021 | 39.0 | 39 | 1.2916 | 0.7273 |
| 0.0579 | 40.0 | 40 | 1.3442 | 0.7273 |
| 0.0579 | 41.0 | 41 | 1.3060 | 0.7273 |
| 0.0579 | 42.0 | 42 | 1.2349 | 0.7273 |
| 0.0579 | 43.0 | 43 | 1.1867 | 0.7273 |
| 0.0579 | 44.0 | 44 | 1.1411 | 0.7273 |
| 0.0579 | 45.0 | 45 | 1.2009 | 0.7273 |
| 0.0579 | 46.0 | 46 | 1.2366 | 0.7273 |
| 0.0579 | 47.0 | 47 | 1.2790 | 0.7273 |
| 0.0579 | 48.0 | 48 | 1.3573 | 0.7273 |
| 0.0579 | 49.0 | 49 | 1.4175 | 0.7273 |
| 0.0436 | 50.0 | 50 | 1.4130 | 0.7273 |
| 0.0436 | 51.0 | 51 | 1.4465 | 0.7273 |
| 0.0436 | 52.0 | 52 | 1.4372 | 0.7273 |
| 0.0436 | 53.0 | 53 | 1.4207 | 0.7273 |
| 0.0436 | 54.0 | 54 | 1.4134 | 0.7273 |
| 0.0436 | 55.0 | 55 | 1.4889 | 0.7273 |
| 0.0436 | 56.0 | 56 | 1.5351 | 0.7273 |
| 0.0436 | 57.0 | 57 | 1.5673 | 0.7273 |
| 0.0436 | 58.0 | 58 | 1.5803 | 0.7273 |
| 0.0436 | 59.0 | 59 | 1.5685 | 0.7273 |
| 0.0325 | 60.0 | 60 | 1.5487 | 0.7273 |
| 0.0325 | 61.0 | 61 | 1.4888 | 0.7273 |
| 0.0325 | 62.0 | 62 | 1.4026 | 0.7273 |
| 0.0325 | 63.0 | 63 | 1.2968 | 0.7273 |
| 0.0325 | 64.0 | 64 | 1.2915 | 0.7273 |
| 0.0325 | 65.0 | 65 | 1.3016 | 0.7273 |
| 0.0325 | 66.0 | 66 | 1.3871 | 0.7273 |
| 0.0325 | 67.0 | 67 | 1.5019 | 0.7273 |
| 0.0325 | 68.0 | 68 | 1.6563 | 0.7273 |
| 0.0325 | 69.0 | 69 | 1.8046 | 0.7273 |
| 0.028 | 70.0 | 70 | 1.9155 | 0.7273 |
| 0.028 | 71.0 | 71 | 1.9688 | 0.7273 |
| 0.028 | 72.0 | 72 | 1.9570 | 0.7273 |
| 0.028 | 73.0 | 73 | 1.8879 | 0.7273 |
| 0.028 | 74.0 | 74 | 1.8354 | 0.7273 |
| 0.028 | 75.0 | 75 | 1.7812 | 0.7273 |
| 0.028 | 76.0 | 76 | 1.6800 | 0.7273 |
| 0.028 | 77.0 | 77 | 1.5444 | 0.7273 |
| 0.028 | 78.0 | 78 | 1.4488 | 0.7273 |
| 0.028 | 79.0 | 79 | 1.3880 | 0.7273 |
| 0.0411 | 80.0 | 80 | 1.3544 | 0.7273 |
| 0.0411 | 81.0 | 81 | 1.3867 | 0.7273 |
| 0.0411 | 82.0 | 82 | 1.4348 | 0.7273 |
| 0.0411 | 83.0 | 83 | 1.4906 | 0.7273 |
| 0.0411 | 84.0 | 84 | 1.5685 | 0.7273 |
| 0.0411 | 85.0 | 85 | 1.6276 | 0.7273 |
| 0.0411 | 86.0 | 86 | 1.6793 | 0.7273 |
| 0.0411 | 87.0 | 87 | 1.7099 | 0.7273 |
| 0.0411 | 88.0 | 88 | 1.7182 | 0.7273 |
| 0.0411 | 89.0 | 89 | 1.7049 | 0.7273 |
| 0.0343 | 90.0 | 90 | 1.6831 | 0.7273 |
| 0.0343 | 91.0 | 91 | 1.6695 | 0.7273 |
| 0.0343 | 92.0 | 92 | 1.6584 | 0.7273 |
| 0.0343 | 93.0 | 93 | 1.6467 | 0.7273 |
| 0.0343 | 94.0 | 94 | 1.6294 | 0.7273 |
| 0.0343 | 95.0 | 95 | 1.6147 | 0.7273 |
| 0.0343 | 96.0 | 96 | 1.6055 | 0.7273 |
| 0.0343 | 97.0 | 97 | 1.6026 | 0.7273 |
| 0.0343 | 98.0 | 98 | 1.6043 | 0.7273 |
| 0.0343 | 99.0 | 99 | 1.6039 | 0.7273 |
| 0.021 | 100.0 | 100 | 1.6044 | 0.7273 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
facebook/deit-base-distilled-patch16-224