metadata
license: apache-2.0
base_model: google/vit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-patch16-224-dmae-va-U3-40A
results: []
vit-base-patch16-224-dmae-va-U3-40A
This model is a fine-tuned version of google/vit-base-patch16-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0213
- Accuracy: 1.0
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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 7 | 1.3292 | 0.3737 |
| 1.3407 | 2.0 | 14 | 1.1079 | 0.5152 |
| 1.3407 | 3.0 | 21 | 0.8918 | 0.6263 |
| 0.9919 | 4.0 | 28 | 0.6447 | 0.7879 |
| 0.9919 | 5.0 | 35 | 0.4502 | 0.8283 |
| 0.5761 | 6.0 | 42 | 0.2720 | 0.9192 |
| 0.3111 | 7.0 | 49 | 0.2302 | 0.9293 |
| 0.3111 | 8.0 | 56 | 0.1650 | 0.9495 |
| 0.204 | 9.0 | 63 | 0.1503 | 0.9495 |
| 0.204 | 10.0 | 70 | 0.0814 | 0.9798 |
| 0.1518 | 11.0 | 77 | 0.0604 | 0.9798 |
| 0.1272 | 12.0 | 84 | 0.1265 | 0.9495 |
| 0.1272 | 13.0 | 91 | 0.0518 | 0.9798 |
| 0.1379 | 14.0 | 98 | 0.0448 | 0.9899 |
| 0.1379 | 15.0 | 105 | 0.0361 | 0.9899 |
| 0.092 | 16.0 | 112 | 0.0322 | 0.9899 |
| 0.092 | 17.0 | 119 | 0.0213 | 1.0 |
| 0.0762 | 18.0 | 126 | 0.0469 | 0.9899 |
| 0.0954 | 19.0 | 133 | 0.0615 | 0.9899 |
| 0.0954 | 20.0 | 140 | 0.0313 | 0.9899 |
| 0.0795 | 21.0 | 147 | 0.0381 | 0.9899 |
| 0.0795 | 22.0 | 154 | 0.0138 | 1.0 |
| 0.077 | 23.0 | 161 | 0.0170 | 1.0 |
| 0.0675 | 24.0 | 168 | 0.0107 | 1.0 |
| 0.0675 | 25.0 | 175 | 0.0193 | 0.9899 |
| 0.0659 | 26.0 | 182 | 0.0255 | 0.9899 |
| 0.0659 | 27.0 | 189 | 0.0201 | 0.9899 |
| 0.0758 | 28.0 | 196 | 0.0325 | 0.9899 |
| 0.0758 | 29.0 | 203 | 0.0110 | 1.0 |
| 0.0589 | 30.0 | 210 | 0.0159 | 1.0 |
| 0.0521 | 31.0 | 217 | 0.0319 | 0.9899 |
| 0.0521 | 32.0 | 224 | 0.0294 | 0.9798 |
| 0.0618 | 33.0 | 231 | 0.0392 | 0.9798 |
| 0.0618 | 34.0 | 238 | 0.0269 | 0.9899 |
| 0.0422 | 35.0 | 245 | 0.0210 | 0.9899 |
| 0.0551 | 36.0 | 252 | 0.0178 | 0.9899 |
| 0.0551 | 37.0 | 259 | 0.0159 | 0.9899 |
| 0.0518 | 38.0 | 266 | 0.0124 | 0.9899 |
| 0.0518 | 39.0 | 273 | 0.0112 | 1.0 |
| 0.0313 | 40.0 | 280 | 0.0110 | 1.0 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2