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---
license: apache-2.0
base_model: microsoft/swinv2-tiny-patch4-window8-256
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swinv2-finetuned-ve-Ub200
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.47058823529411764
---
<!-- 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-finetuned-ve-Ub200
This model is a fine-tuned version of [microsoft/swinv2-tiny-patch4-window8-256](https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5977
- Accuracy: 0.4706
## 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: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 0.92 | 6 | 7.9891 | 0.0980 |
| No log | 2.0 | 13 | 7.4848 | 0.0980 |
| No log | 2.92 | 19 | 6.2378 | 0.0980 |
| No log | 4.0 | 26 | 4.8900 | 0.0980 |
| No log | 4.92 | 32 | 3.8155 | 0.0980 |
| No log | 6.0 | 39 | 2.7342 | 0.0980 |
| No log | 6.92 | 45 | 2.0612 | 0.0980 |
| No log | 8.0 | 52 | 1.5977 | 0.4706 |
| No log | 8.92 | 58 | 1.3671 | 0.4706 |
| No log | 10.0 | 65 | 1.2122 | 0.4706 |
| No log | 10.92 | 71 | 1.1823 | 0.4706 |
| No log | 12.0 | 78 | 1.1835 | 0.4706 |
| No log | 12.92 | 84 | 1.1838 | 0.4706 |
| No log | 14.0 | 91 | 1.1778 | 0.4706 |
| No log | 14.92 | 97 | 1.1769 | 0.4706 |
| 3.2267 | 16.0 | 104 | 1.1762 | 0.4706 |
| 3.2267 | 16.92 | 110 | 1.1758 | 0.4706 |
| 3.2267 | 18.0 | 117 | 1.1770 | 0.4706 |
| 3.2267 | 18.46 | 120 | 1.1771 | 0.4706 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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