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---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: S5_M1_fold3_swint_42500769
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: 0.9968404423380727
---
<!-- 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. -->
# S5_M1_fold3_swint_42500769
This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0158
- Accuracy: 0.9968
## 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0382 | 1.0 | 79 | 0.0472 | 0.9897 |
| 0.0065 | 1.99 | 158 | 0.0091 | 0.9968 |
| 0.0496 | 2.99 | 237 | 0.0103 | 0.9961 |
| 0.0003 | 4.0 | 317 | 0.0107 | 0.9968 |
| 0.0002 | 4.98 | 395 | 0.0158 | 0.9968 |
### Framework versions
- Transformers 4.36.2
- Pytorch 1.11.0+cu102
- Datasets 2.16.0
- Tokenizers 0.15.0