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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-U5-42
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-U5-42
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: 0.6806
- Accuracy: 0.8333
## 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: 42
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.9 | 7 | 1.3299 | 0.4 |
| 1.3678 | 1.94 | 15 | 1.2662 | 0.45 |
| 1.3678 | 2.97 | 23 | 1.0959 | 0.5167 |
| 1.2546 | 4.0 | 31 | 0.9759 | 0.55 |
| 1.0271 | 4.9 | 38 | 0.9375 | 0.5667 |
| 1.0271 | 5.94 | 46 | 0.8728 | 0.6 |
| 0.8075 | 6.97 | 54 | 0.7360 | 0.7167 |
| 0.7026 | 8.0 | 62 | 0.8097 | 0.6667 |
| 0.7026 | 8.9 | 69 | 0.7074 | 0.7 |
| 0.5711 | 9.94 | 77 | 0.6913 | 0.7833 |
| 0.5063 | 10.97 | 85 | 0.7462 | 0.7167 |
| 0.5063 | 12.0 | 93 | 0.8509 | 0.5833 |
| 0.4701 | 12.9 | 100 | 0.6895 | 0.7333 |
| 0.3708 | 13.94 | 108 | 0.7593 | 0.6833 |
| 0.3708 | 14.97 | 116 | 0.8622 | 0.7167 |
| 0.3581 | 16.0 | 124 | 0.7504 | 0.7667 |
| 0.3581 | 16.9 | 131 | 0.6694 | 0.75 |
| 0.3342 | 17.94 | 139 | 0.7262 | 0.7333 |
| 0.2979 | 18.97 | 147 | 0.7234 | 0.7167 |
| 0.2979 | 20.0 | 155 | 0.6403 | 0.7833 |
| 0.2919 | 20.9 | 162 | 0.6847 | 0.7667 |
| 0.274 | 21.94 | 170 | 0.6943 | 0.75 |
| 0.274 | 22.97 | 178 | 0.7235 | 0.7833 |
| 0.2434 | 24.0 | 186 | 0.7836 | 0.75 |
| 0.239 | 24.9 | 193 | 0.7199 | 0.8167 |
| 0.239 | 25.94 | 201 | 0.6806 | 0.8333 |
| 0.2184 | 26.97 | 209 | 0.6923 | 0.8 |
| 0.2176 | 28.0 | 217 | 0.7070 | 0.7833 |
| 0.2176 | 28.9 | 224 | 0.6991 | 0.7667 |
| 0.231 | 29.94 | 232 | 0.7043 | 0.7833 |
| 0.1889 | 30.97 | 240 | 0.6575 | 0.7667 |
| 0.1889 | 32.0 | 248 | 0.7521 | 0.75 |
| 0.2033 | 32.9 | 255 | 0.7062 | 0.7833 |
| 0.2033 | 33.94 | 263 | 0.6958 | 0.8 |
| 0.1891 | 34.97 | 271 | 0.7189 | 0.8 |
| 0.1739 | 36.0 | 279 | 0.7457 | 0.8 |
| 0.1739 | 36.9 | 286 | 0.7766 | 0.7833 |
| 0.1949 | 37.94 | 294 | 0.7808 | 0.7667 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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