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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-tiny-patch4-window8-256-Diabetic-Retinopathy-DA
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: 0.8090909090909091
---
<!-- 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-Diabetic-Retinopathy-DA
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: 0.6974
- Accuracy: 0.8091
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5987 | 1.0 | 23 | 1.5683 | 0.4909 |
| 1.4137 | 2.0 | 46 | 1.2639 | 0.4909 |
| 1.1988 | 3.0 | 69 | 0.8726 | 0.7636 |
| 0.8533 | 4.0 | 92 | 0.6361 | 0.7545 |
| 0.8042 | 5.0 | 115 | 0.5985 | 0.7545 |
| 0.7349 | 6.0 | 138 | 0.5943 | 0.7545 |
| 0.7003 | 7.0 | 161 | 0.5178 | 0.7636 |
| 0.6641 | 8.0 | 184 | 0.5058 | 0.7545 |
| 0.641 | 9.0 | 207 | 0.5092 | 0.7909 |
| 0.6571 | 10.0 | 230 | 0.5319 | 0.7636 |
| 0.6522 | 11.0 | 253 | 0.5726 | 0.7909 |
| 0.5659 | 12.0 | 276 | 0.5490 | 0.7727 |
| 0.5511 | 13.0 | 299 | 0.5465 | 0.8 |
| 0.5435 | 14.0 | 322 | 0.5728 | 0.7909 |
| 0.5259 | 15.0 | 345 | 0.6047 | 0.7636 |
| 0.5496 | 16.0 | 368 | 0.6479 | 0.7818 |
| 0.543 | 17.0 | 391 | 0.6040 | 0.7727 |
| 0.4646 | 18.0 | 414 | 0.6269 | 0.7818 |
| 0.4867 | 19.0 | 437 | 0.6535 | 0.7909 |
| 0.4357 | 20.0 | 460 | 0.6991 | 0.7727 |
| 0.4392 | 21.0 | 483 | 0.7127 | 0.7636 |
| 0.4403 | 22.0 | 506 | 0.6974 | 0.8091 |
| 0.4358 | 23.0 | 529 | 0.6883 | 0.7818 |
| 0.4094 | 24.0 | 552 | 0.6768 | 0.8 |
| 0.3913 | 25.0 | 575 | 0.7270 | 0.7636 |
| 0.3686 | 26.0 | 598 | 0.7104 | 0.7727 |
| 0.3679 | 27.0 | 621 | 0.7115 | 0.7818 |
| 0.378 | 28.0 | 644 | 0.8020 | 0.8091 |
| 0.3583 | 29.0 | 667 | 0.7524 | 0.7909 |
| 0.3299 | 30.0 | 690 | 0.7783 | 0.7909 |
| 0.3672 | 31.0 | 713 | 0.8193 | 0.7909 |
| 0.3567 | 32.0 | 736 | 0.8095 | 0.7909 |
| 0.3585 | 33.0 | 759 | 0.8324 | 0.7909 |
| 0.3191 | 34.0 | 782 | 0.8042 | 0.7909 |
| 0.3144 | 35.0 | 805 | 0.8189 | 0.7909 |
| 0.3452 | 36.0 | 828 | 0.8377 | 0.7909 |
| 0.3263 | 37.0 | 851 | 0.8204 | 0.7909 |
| 0.2939 | 38.0 | 874 | 0.8103 | 0.7909 |
| 0.3152 | 39.0 | 897 | 0.8184 | 0.7818 |
| 0.2787 | 40.0 | 920 | 0.8241 | 0.7818 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0
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