File size: 3,817 Bytes
b705204 d11c5f5 b705204 2f08804 b705204 b6011ca b705204 d11c5f5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 |
---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-dmae-va-U
results: []
datasets:
- Augusto777/dmae-U
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-dmae-va-U
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an AMD dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0900
- Accuracy: 0.9725
## 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 | 0.9 | 7 | 1.4643 | 0.2110 |
| 1.4218 | 1.94 | 15 | 1.4070 | 0.3303 |
| 1.3226 | 2.97 | 23 | 1.3454 | 0.3486 |
| 1.1908 | 4.0 | 31 | 1.1438 | 0.4220 |
| 1.1908 | 4.9 | 38 | 0.8730 | 0.5780 |
| 0.9441 | 5.94 | 46 | 0.8100 | 0.6422 |
| 0.7185 | 6.97 | 54 | 0.6099 | 0.7339 |
| 0.6526 | 8.0 | 62 | 0.5096 | 0.7890 |
| 0.6526 | 8.9 | 69 | 0.4925 | 0.8165 |
| 0.5185 | 9.94 | 77 | 0.3989 | 0.8349 |
| 0.4946 | 10.97 | 85 | 0.3276 | 0.8807 |
| 0.4469 | 12.0 | 93 | 0.3023 | 0.8899 |
| 0.376 | 12.9 | 100 | 0.3112 | 0.8991 |
| 0.376 | 13.94 | 108 | 0.2117 | 0.9266 |
| 0.3156 | 14.97 | 116 | 0.2024 | 0.9174 |
| 0.366 | 16.0 | 124 | 0.2065 | 0.9450 |
| 0.2806 | 16.9 | 131 | 0.1942 | 0.9174 |
| 0.2806 | 17.94 | 139 | 0.2393 | 0.9174 |
| 0.2695 | 18.97 | 147 | 0.1498 | 0.9541 |
| 0.2357 | 20.0 | 155 | 0.1465 | 0.9358 |
| 0.2345 | 20.9 | 162 | 0.1522 | 0.9633 |
| 0.2157 | 21.94 | 170 | 0.1403 | 0.9450 |
| 0.2157 | 22.97 | 178 | 0.0999 | 0.9541 |
| 0.1894 | 24.0 | 186 | 0.1427 | 0.9633 |
| 0.2195 | 24.9 | 193 | 0.0949 | 0.9633 |
| 0.1874 | 25.94 | 201 | 0.1152 | 0.9633 |
| 0.1874 | 26.97 | 209 | 0.1226 | 0.9541 |
| 0.1815 | 28.0 | 217 | 0.0964 | 0.9633 |
| 0.1619 | 28.9 | 224 | 0.0912 | 0.9633 |
| 0.201 | 29.94 | 232 | 0.0903 | 0.9633 |
| 0.1659 | 30.97 | 240 | 0.0745 | 0.9633 |
| 0.1659 | 32.0 | 248 | 0.0781 | 0.9633 |
| 0.1459 | 32.9 | 255 | 0.0930 | 0.9633 |
| 0.1459 | 33.94 | 263 | 0.0900 | 0.9725 |
| 0.1487 | 34.97 | 271 | 0.0796 | 0.9725 |
| 0.1487 | 36.0 | 279 | 0.0784 | 0.9725 |
| 0.1504 | 36.13 | 280 | 0.0784 | 0.9725 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0 |