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---
license: apache-2.0
base_model: microsoft/swinv2-base-patch4-window12-192-22k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 0.50-200Train-100Test-swinv2-base
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. -->
# 0.50-200Train-100Test-swinv2-base
This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window12-192-22k](https://huggingface.co/microsoft/swinv2-base-patch4-window12-192-22k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1459
- Accuracy: 0.8183
## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 17
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.7214 | 0.9931 | 36 | 1.0786 | 0.6515 |
| 0.6184 | 1.9862 | 72 | 0.7491 | 0.7651 |
| 0.357 | 2.9793 | 108 | 0.7632 | 0.7764 |
| 0.2085 | 4.0 | 145 | 0.8125 | 0.7860 |
| 0.1343 | 4.9931 | 181 | 0.7920 | 0.7974 |
| 0.0641 | 5.9862 | 217 | 0.8851 | 0.7860 |
| 0.0515 | 6.9793 | 253 | 1.0784 | 0.7817 |
| 0.041 | 8.0 | 290 | 1.0600 | 0.7965 |
| 0.0338 | 8.9931 | 326 | 1.0860 | 0.8131 |
| 0.013 | 9.9862 | 362 | 1.0956 | 0.8148 |
| 0.016 | 10.9793 | 398 | 1.2115 | 0.7991 |
| 0.0154 | 12.0 | 435 | 1.1470 | 0.8105 |
| 0.011 | 12.9931 | 471 | 1.1045 | 0.8105 |
| 0.0027 | 13.9862 | 507 | 1.1310 | 0.8096 |
| 0.0042 | 14.9793 | 543 | 1.1808 | 0.8227 |
| 0.0016 | 16.0 | 580 | 1.1575 | 0.8157 |
| 0.0007 | 16.8828 | 612 | 1.1459 | 0.8183 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
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