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vit-base-patch16-224-dmae-va-da-40C
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: 0.3208
- Accuracy: 0.9302
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 | 3 | 1.3666 | 0.2093 |
| No log | 1.85 | 6 | 1.3164 | 0.2558 |
| 1.3006 | 2.77 | 9 | 1.2166 | 0.4186 |
| 1.3006 | 4.0 | 13 | 0.9618 | 0.5581 |
| 0.9554 | 4.92 | 16 | 0.8278 | 0.6279 |
| 0.9554 | 5.85 | 19 | 0.7054 | 0.7442 |
| 0.9554 | 6.77 | 22 | 0.6724 | 0.7209 |
| 0.6343 | 8.0 | 26 | 0.6016 | 0.7442 |
| 0.6343 | 8.92 | 29 | 0.5518 | 0.7674 |
| 0.4376 | 9.85 | 32 | 0.4945 | 0.8140 |
| 0.4376 | 10.77 | 35 | 0.5047 | 0.8140 |
| 0.4376 | 12.0 | 39 | 0.4657 | 0.8372 |
| 0.2915 | 12.92 | 42 | 0.4190 | 0.8372 |
| 0.2915 | 13.85 | 45 | 0.4187 | 0.8837 |
| 0.2197 | 14.77 | 48 | 0.3822 | 0.8837 |
| 0.2197 | 16.0 | 52 | 0.3720 | 0.8605 |
| 0.2197 | 16.92 | 55 | 0.3161 | 0.8605 |
| 0.2065 | 17.85 | 58 | 0.3437 | 0.8605 |
| 0.2065 | 18.77 | 61 | 0.3175 | 0.8605 |
| 0.1273 | 20.0 | 65 | 0.3571 | 0.8837 |
| 0.1273 | 20.92 | 68 | 0.3465 | 0.8837 |
| 0.1273 | 21.85 | 71 | 0.3042 | 0.8837 |
| 0.1164 | 22.77 | 74 | 0.3009 | 0.8837 |
| 0.1164 | 24.0 | 78 | 0.3373 | 0.9070 |
| 0.1154 | 24.92 | 81 | 0.2979 | 0.9070 |
| 0.1154 | 25.85 | 84 | 0.2799 | 0.9070 |
| 0.1154 | 26.77 | 87 | 0.2848 | 0.9070 |
| 0.1331 | 28.0 | 91 | 0.3093 | 0.9070 |
| 0.1331 | 28.92 | 94 | 0.3208 | 0.9302 |
| 0.0881 | 29.85 | 97 | 0.2996 | 0.9302 |
| 0.0881 | 30.77 | 100 | 0.2708 | 0.9302 |
| 0.0862 | 32.0 | 104 | 0.2588 | 0.9302 |
| 0.0862 | 32.92 | 107 | 0.2619 | 0.9302 |
| 0.0862 | 33.85 | 110 | 0.2761 | 0.9070 |
| 0.0578 | 34.77 | 113 | 0.2898 | 0.9070 |
| 0.0578 | 36.0 | 117 | 0.2994 | 0.9070 |
| 0.1087 | 36.92 | 120 | 0.3013 | 0.9070 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
