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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-U5-42C
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-U5-42C
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: 0.7073
- Accuracy: 0.7667
## 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: 1e-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 | 0.9032 | 7 | 1.3926 | 0.35 |
| 1.4087 | 1.9355 | 15 | 1.3365 | 0.4167 |
| 1.3807 | 2.9677 | 23 | 1.2813 | 0.4167 |
| 1.35 | 4.0 | 31 | 1.2407 | 0.4 |
| 1.35 | 4.9032 | 38 | 1.2116 | 0.4833 |
| 1.2933 | 5.9355 | 46 | 1.1653 | 0.4833 |
| 1.2426 | 6.9677 | 54 | 1.1151 | 0.5167 |
| 1.1771 | 8.0 | 62 | 1.0441 | 0.6 |
| 1.1771 | 8.9032 | 69 | 0.9990 | 0.5667 |
| 1.0983 | 9.9355 | 77 | 0.9456 | 0.6333 |
| 1.0338 | 10.9677 | 85 | 0.9160 | 0.6833 |
| 0.9665 | 12.0 | 93 | 0.8940 | 0.6833 |
| 0.9133 | 12.9032 | 100 | 0.8753 | 0.6 |
| 0.9133 | 13.9355 | 108 | 0.8518 | 0.6667 |
| 0.8521 | 14.9677 | 116 | 0.8515 | 0.65 |
| 0.8461 | 16.0 | 124 | 0.8407 | 0.65 |
| 0.808 | 16.9032 | 131 | 0.8218 | 0.65 |
| 0.808 | 17.9355 | 139 | 0.8170 | 0.6833 |
| 0.7779 | 18.9677 | 147 | 0.7972 | 0.7167 |
| 0.758 | 20.0 | 155 | 0.7817 | 0.7333 |
| 0.7416 | 20.9032 | 162 | 0.7678 | 0.7167 |
| 0.7344 | 21.9355 | 170 | 0.7650 | 0.7167 |
| 0.7344 | 22.9677 | 178 | 0.7428 | 0.7333 |
| 0.7091 | 24.0 | 186 | 0.7280 | 0.75 |
| 0.6876 | 24.9032 | 193 | 0.7235 | 0.75 |
| 0.6887 | 25.9355 | 201 | 0.7278 | 0.75 |
| 0.6887 | 26.9677 | 209 | 0.7264 | 0.75 |
| 0.6897 | 28.0 | 217 | 0.7228 | 0.75 |
| 0.6637 | 28.9032 | 224 | 0.7163 | 0.75 |
| 0.6924 | 29.9355 | 232 | 0.7073 | 0.7667 |
| 0.6234 | 30.9677 | 240 | 0.7057 | 0.7667 |
| 0.6234 | 32.0 | 248 | 0.7090 | 0.7667 |
| 0.6652 | 32.9032 | 255 | 0.7052 | 0.7667 |
| 0.6343 | 33.9355 | 263 | 0.7009 | 0.7667 |
| 0.6327 | 34.9677 | 271 | 0.7017 | 0.7667 |
| 0.6327 | 36.0 | 279 | 0.7023 | 0.7667 |
| 0.6339 | 36.9032 | 286 | 0.7027 | 0.7667 |
| 0.6275 | 37.9355 | 294 | 0.7031 | 0.7667 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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