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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-humeda-2
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-humeda-2
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: 0.7928
- Accuracy: 0.7115
## 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 | 1.0 | 2 | 1.3469 | 0.5 |
| No log | 2.0 | 4 | 1.3200 | 0.4808 |
| No log | 3.0 | 6 | 1.3124 | 0.4808 |
| No log | 4.0 | 8 | 1.2178 | 0.5 |
| 1.1551 | 5.0 | 10 | 1.0957 | 0.5769 |
| 1.1551 | 6.0 | 12 | 1.0359 | 0.5769 |
| 1.1551 | 7.0 | 14 | 1.0103 | 0.5962 |
| 1.1551 | 8.0 | 16 | 0.9382 | 0.6538 |
| 1.1551 | 9.0 | 18 | 0.8748 | 0.6346 |
| 0.9827 | 10.0 | 20 | 0.8836 | 0.6154 |
| 0.9827 | 11.0 | 22 | 0.8574 | 0.6154 |
| 0.9827 | 12.0 | 24 | 0.8494 | 0.5962 |
| 0.9827 | 13.0 | 26 | 0.8226 | 0.6154 |
| 0.9827 | 14.0 | 28 | 0.8242 | 0.6346 |
| 0.8007 | 15.0 | 30 | 0.8304 | 0.6154 |
| 0.8007 | 16.0 | 32 | 0.8447 | 0.6538 |
| 0.8007 | 17.0 | 34 | 0.8228 | 0.6923 |
| 0.8007 | 18.0 | 36 | 0.7928 | 0.7115 |
| 0.8007 | 19.0 | 38 | 0.7822 | 0.6731 |
| 0.6882 | 20.0 | 40 | 0.7750 | 0.6538 |
| 0.6882 | 21.0 | 42 | 0.7726 | 0.6538 |
| 0.6882 | 22.0 | 44 | 0.7898 | 0.6731 |
| 0.6882 | 23.0 | 46 | 0.8021 | 0.6731 |
| 0.6882 | 24.0 | 48 | 0.7834 | 0.6923 |
| 0.6154 | 25.0 | 50 | 0.7634 | 0.6731 |
| 0.6154 | 26.0 | 52 | 0.7584 | 0.6923 |
| 0.6154 | 27.0 | 54 | 0.7773 | 0.6538 |
| 0.6154 | 28.0 | 56 | 0.7830 | 0.6538 |
| 0.6154 | 29.0 | 58 | 0.7719 | 0.6538 |
| 0.541 | 30.0 | 60 | 0.7603 | 0.6538 |
| 0.541 | 31.0 | 62 | 0.7497 | 0.6731 |
| 0.541 | 32.0 | 64 | 0.7381 | 0.7115 |
| 0.541 | 33.0 | 66 | 0.7275 | 0.6923 |
| 0.541 | 34.0 | 68 | 0.7277 | 0.6923 |
| 0.5163 | 35.0 | 70 | 0.7271 | 0.6923 |
| 0.5163 | 36.0 | 72 | 0.7274 | 0.6923 |
| 0.5163 | 37.0 | 74 | 0.7304 | 0.6923 |
| 0.5163 | 38.0 | 76 | 0.7329 | 0.6923 |
| 0.5163 | 39.0 | 78 | 0.7351 | 0.6923 |
| 0.5183 | 40.0 | 80 | 0.7356 | 0.6923 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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