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---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finalterm
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9313077939233818
---
<!-- 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. -->
# swin-tiny-patch4-window7-224-finalterm
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1837
- Accuracy: 0.9313
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.2727 | 0.9684 | 23 | 0.5536 | 0.8336 |
| 0.3845 | 1.9789 | 47 | 0.2386 | 0.9115 |
| 0.2725 | 2.9895 | 71 | 0.2135 | 0.9234 |
| 0.2442 | 4.0 | 95 | 0.2291 | 0.9075 |
| 0.2097 | 4.9684 | 118 | 0.1964 | 0.9207 |
| 0.2237 | 5.9789 | 142 | 0.1920 | 0.9287 |
| 0.2199 | 6.9895 | 166 | 0.1844 | 0.9353 |
| 0.2209 | 8.0 | 190 | 0.1857 | 0.9273 |
| 0.1717 | 8.9684 | 213 | 0.1842 | 0.9313 |
| 0.1754 | 9.6842 | 230 | 0.1837 | 0.9313 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
|