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---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: swinv2-tiny-patch4-window8-256-dmae-va-U5-42B
results: []
---
<!-- 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. -->
# swinv2-tiny-patch4-window8-256-dmae-va-U5-42B
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8386
- Accuracy: 0.65
## 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: 4e-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: 42
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.9 | 7 | 6.1748 | 0.1167 |
| 5.327 | 1.94 | 15 | 6.0660 | 0.1167 |
| 5.327 | 2.97 | 23 | 5.4902 | 0.1167 |
| 5.0963 | 4.0 | 31 | 4.2768 | 0.1167 |
| 3.9193 | 4.9 | 38 | 3.0013 | 0.1167 |
| 3.9193 | 5.94 | 46 | 1.9289 | 0.1167 |
| 2.2222 | 6.97 | 54 | 1.3857 | 0.1167 |
| 1.4465 | 8.0 | 62 | 1.3423 | 0.4333 |
| 1.4465 | 8.9 | 69 | 1.2786 | 0.45 |
| 1.3709 | 9.94 | 77 | 1.2654 | 0.4667 |
| 1.3511 | 10.97 | 85 | 1.2605 | 0.4667 |
| 1.3511 | 12.0 | 93 | 1.2184 | 0.4667 |
| 1.2749 | 12.9 | 100 | 1.2894 | 0.5 |
| 1.222 | 13.94 | 108 | 1.2072 | 0.5167 |
| 1.222 | 14.97 | 116 | 1.1749 | 0.5167 |
| 1.1668 | 16.0 | 124 | 1.1988 | 0.5167 |
| 1.1668 | 16.9 | 131 | 1.2306 | 0.5167 |
| 1.101 | 17.94 | 139 | 1.1432 | 0.5333 |
| 1.029 | 18.97 | 147 | 1.0208 | 0.55 |
| 1.029 | 20.0 | 155 | 0.9577 | 0.6167 |
| 0.9403 | 20.9 | 162 | 0.9479 | 0.5 |
| 0.8887 | 21.94 | 170 | 0.8910 | 0.5833 |
| 0.8887 | 22.97 | 178 | 0.9442 | 0.5333 |
| 0.8506 | 24.0 | 186 | 0.8923 | 0.6 |
| 0.8064 | 24.9 | 193 | 0.8973 | 0.6 |
| 0.8064 | 25.94 | 201 | 0.9079 | 0.55 |
| 0.7434 | 26.97 | 209 | 0.8386 | 0.65 |
| 0.7404 | 28.0 | 217 | 0.8645 | 0.6167 |
| 0.7404 | 28.9 | 224 | 0.8599 | 0.5667 |
| 0.7215 | 29.94 | 232 | 0.8420 | 0.65 |
| 0.6743 | 30.97 | 240 | 0.8553 | 0.5667 |
| 0.6743 | 32.0 | 248 | 0.8355 | 0.6167 |
| 0.6767 | 32.9 | 255 | 0.8694 | 0.5833 |
| 0.6767 | 33.94 | 263 | 0.8559 | 0.65 |
| 0.6606 | 34.97 | 271 | 0.8351 | 0.6167 |
| 0.6488 | 36.0 | 279 | 0.8287 | 0.6333 |
| 0.6488 | 36.9 | 286 | 0.8377 | 0.6167 |
| 0.6544 | 37.94 | 294 | 0.8406 | 0.6 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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