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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: cards-top_right_swin-tiny-patch4-window7-224-finetuned-v2_more_data
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.6269272417882741
---
<!-- 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. -->
# cards-top_right_swin-tiny-patch4-window7-224-finetuned-v2_more_data
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: 0.9268
- Accuracy: 0.6269
## 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: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.4585 | 1.0 | 1363 | 1.2999 | 0.4337 |
| 1.4211 | 2.0 | 2726 | 1.1663 | 0.4927 |
| 1.4203 | 3.0 | 4089 | 1.0770 | 0.5312 |
| 1.4669 | 4.0 | 5453 | 1.0744 | 0.5496 |
| 1.3781 | 5.0 | 6816 | 1.0245 | 0.5599 |
| 1.3852 | 6.0 | 8179 | 1.0645 | 0.5402 |
| 1.3407 | 7.0 | 9542 | 1.0011 | 0.5696 |
| 1.3727 | 8.0 | 10906 | 0.9898 | 0.5801 |
| 1.328 | 9.0 | 12269 | 0.9965 | 0.5738 |
| 1.3374 | 10.0 | 13632 | 0.9722 | 0.5874 |
| 1.3513 | 11.0 | 14995 | 0.9632 | 0.5873 |
| 1.3728 | 12.0 | 16359 | 0.9818 | 0.5802 |
| 1.3289 | 13.0 | 17722 | 0.9845 | 0.5729 |
| 1.3219 | 14.0 | 19085 | 0.9633 | 0.5881 |
| 1.2893 | 15.0 | 20448 | 0.9312 | 0.6004 |
| 1.3088 | 16.0 | 21812 | 0.9537 | 0.5903 |
| 1.3252 | 17.0 | 23175 | 0.9432 | 0.5986 |
| 1.3424 | 18.0 | 24538 | 0.9291 | 0.5979 |
| 1.3077 | 19.0 | 25901 | 0.9245 | 0.6020 |
| 1.2466 | 20.0 | 27265 | 0.9304 | 0.6039 |
| 1.2767 | 21.0 | 28628 | 0.9122 | 0.6099 |
| 1.2553 | 22.0 | 29991 | 0.9312 | 0.6005 |
| 1.2698 | 23.0 | 31354 | 0.9137 | 0.6092 |
| 1.2591 | 24.0 | 32718 | 0.9113 | 0.6134 |
| 1.277 | 25.0 | 34081 | 0.9095 | 0.6142 |
| 1.2742 | 26.0 | 35444 | 0.9227 | 0.6100 |
| 1.222 | 27.0 | 36807 | 0.9090 | 0.6147 |
| 1.2368 | 28.0 | 38171 | 0.9020 | 0.6172 |
| 1.198 | 29.0 | 39534 | 0.9071 | 0.6157 |
| 1.2076 | 30.0 | 40897 | 0.9031 | 0.6214 |
| 1.212 | 31.0 | 42260 | 0.9136 | 0.6175 |
| 1.2105 | 32.0 | 43624 | 0.9170 | 0.6151 |
| 1.2687 | 33.0 | 44987 | 0.9047 | 0.6186 |
| 1.2038 | 34.0 | 46350 | 0.9061 | 0.6190 |
| 1.1957 | 35.0 | 47713 | 0.9052 | 0.6255 |
| 1.1962 | 36.0 | 49077 | 0.9057 | 0.6210 |
| 1.1866 | 37.0 | 50440 | 0.9105 | 0.6227 |
| 1.2545 | 38.0 | 51803 | 0.9173 | 0.6206 |
| 1.1642 | 39.0 | 53166 | 0.9120 | 0.6239 |
| 1.1711 | 40.0 | 54530 | 0.9235 | 0.6177 |
| 1.2339 | 41.0 | 55893 | 0.9295 | 0.6143 |
| 1.1132 | 42.0 | 57256 | 0.9143 | 0.6234 |
| 1.1977 | 43.0 | 58619 | 0.9163 | 0.6256 |
| 1.1617 | 44.0 | 59983 | 0.9246 | 0.6233 |
| 1.1357 | 45.0 | 61346 | 0.9196 | 0.6255 |
| 1.1362 | 46.0 | 62709 | 0.9221 | 0.6259 |
| 1.1472 | 47.0 | 64072 | 0.9206 | 0.6263 |
| 1.184 | 48.0 | 65436 | 0.9282 | 0.6256 |
| 1.1096 | 49.0 | 66799 | 0.9252 | 0.6269 |
| 1.1425 | 49.99 | 68150 | 0.9268 | 0.6269 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2
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