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-U5-40
results: []
datasets:
- Augusto777/dmae-ve-U5
vit-base-patch16-224-dmae-va-U5-40
This model is a fine-tuned version of google/vit-base-patch16-224 on Augusto777/dmae-ve-U5 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0367
- Accuracy: 0.8166
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 | 0.92 | 6 | 1.4236 | 0.3605 |
| 1.3165 | 2.0 | 13 | 1.1072 | 0.5306 |
| 1.3165 | 2.92 | 19 | 0.9370 | 0.6463 |
| 0.93 | 4.0 | 26 | 0.6870 | 0.7687 |
| 0.93 | 4.92 | 32 | 0.4743 | 0.8163 |
| 0.5368 | 6.0 | 39 | 0.2825 | 0.9184 |
| 0.5368 | 6.92 | 45 | 0.2066 | 0.9524 |
| 0.2989 | 8.0 | 52 | 0.1224 | 0.9728 |
| 0.2989 | 8.92 | 58 | 0.1453 | 0.9592 |
| 0.1746 | 10.0 | 65 | 0.0367 | 1.0 |
| 0.1746 | 10.92 | 71 | 0.0616 | 0.9864 |
| 0.1596 | 12.0 | 78 | 0.0234 | 1.0 |
| 0.1094 | 12.92 | 84 | 0.0298 | 1.0 |
| 0.1094 | 14.0 | 91 | 0.0444 | 0.9932 |
| 0.1123 | 14.92 | 97 | 0.0251 | 1.0 |
| 0.1123 | 16.0 | 104 | 0.0185 | 1.0 |
| 0.0761 | 16.92 | 110 | 0.0159 | 1.0 |
| 0.0761 | 18.0 | 117 | 0.0180 | 1.0 |
| 0.0743 | 18.92 | 123 | 0.0111 | 1.0 |
| 0.0743 | 20.0 | 130 | 0.0134 | 1.0 |
| 0.072 | 20.92 | 136 | 0.0123 | 1.0 |
| 0.072 | 22.0 | 143 | 0.0100 | 1.0 |
| 0.0744 | 22.92 | 149 | 0.0074 | 1.0 |
| 0.0688 | 24.0 | 156 | 0.0064 | 1.0 |
| 0.0688 | 24.92 | 162 | 0.0070 | 1.0 |
| 0.0737 | 26.0 | 169 | 0.0064 | 1.0 |
| 0.0737 | 26.92 | 175 | 0.0055 | 1.0 |
| 0.053 | 28.0 | 182 | 0.0075 | 1.0 |
| 0.053 | 28.92 | 188 | 0.0046 | 1.0 |
| 0.0677 | 30.0 | 195 | 0.0046 | 1.0 |
| 0.0677 | 30.92 | 201 | 0.0098 | 1.0 |
| 0.055 | 32.0 | 208 | 0.0085 | 1.0 |
| 0.055 | 32.92 | 214 | 0.0056 | 1.0 |
| 0.0576 | 34.0 | 221 | 0.0059 | 1.0 |
| 0.0576 | 34.92 | 227 | 0.0054 | 1.0 |
| 0.0697 | 36.0 | 234 | 0.0055 | 1.0 |
| 0.0415 | 36.92 | 240 | 0.0056 | 1.0 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2