---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: cards_bottom_left_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: 0.5927874941959449
---

<!-- 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_bottom_left_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: 1.0009
- Accuracy: 0.5928

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.559         | 1.0   | 1362  | 1.3402          | 0.4189   |
| 1.5165        | 2.0   | 2725  | 1.2308          | 0.4647   |
| 1.484         | 3.0   | 4087  | 1.1676          | 0.4954   |
| 1.5037        | 4.0   | 5450  | 1.1206          | 0.5198   |
| 1.4489        | 5.0   | 6812  | 1.1162          | 0.5284   |
| 1.4335        | 6.0   | 8175  | 1.1395          | 0.5047   |
| 1.4281        | 7.0   | 9537  | 1.0606          | 0.5445   |
| 1.4219        | 8.0   | 10900 | 1.0754          | 0.5408   |
| 1.3935        | 9.0   | 12262 | 1.0285          | 0.5604   |
| 1.3542        | 10.0  | 13625 | 1.0497          | 0.5453   |
| 1.3761        | 11.0  | 14987 | 1.0535          | 0.5450   |
| 1.3824        | 12.0  | 16350 | 1.0268          | 0.5591   |
| 1.3709        | 13.0  | 17712 | 1.0015          | 0.5690   |
| 1.3361        | 14.0  | 19075 | 1.0266          | 0.5595   |
| 1.3673        | 15.0  | 20437 | 0.9988          | 0.5772   |
| 1.376         | 16.0  | 21800 | 0.9950          | 0.5744   |
| 1.3486        | 17.0  | 23162 | 0.9837          | 0.5784   |
| 1.3333        | 18.0  | 24525 | 0.9771          | 0.5827   |
| 1.347         | 19.0  | 25887 | 0.9895          | 0.5770   |
| 1.3381        | 20.0  | 27250 | 0.9709          | 0.5820   |
| 1.3385        | 21.0  | 28612 | 0.9704          | 0.5833   |
| 1.336         | 22.0  | 29975 | 0.9646          | 0.5885   |
| 1.3372        | 23.0  | 31337 | 0.9653          | 0.5879   |
| 1.2979        | 24.0  | 32700 | 0.9867          | 0.5814   |
| 1.2948        | 25.0  | 34062 | 0.9633          | 0.5870   |
| 1.2767        | 26.0  | 35425 | 0.9578          | 0.5877   |
| 1.3012        | 27.0  | 36787 | 0.9709          | 0.5867   |
| 1.2667        | 28.0  | 38150 | 0.9648          | 0.5899   |
| 1.3           | 29.0  | 39512 | 0.9560          | 0.5930   |
| 1.2735        | 30.0  | 40875 | 0.9595          | 0.5949   |
| 1.2895        | 31.0  | 42237 | 0.9851          | 0.5809   |
| 1.2234        | 32.0  | 43600 | 0.9601          | 0.5931   |
| 1.2212        | 33.0  | 44962 | 0.9800          | 0.5917   |
| 1.2483        | 34.0  | 46325 | 0.9662          | 0.5982   |
| 1.2507        | 35.0  | 47687 | 0.9657          | 0.5910   |
| 1.2539        | 36.0  | 49050 | 0.9954          | 0.5783   |
| 1.2491        | 37.0  | 50412 | 0.9718          | 0.5924   |
| 1.2397        | 38.0  | 51775 | 0.9769          | 0.5930   |
| 1.1903        | 39.0  | 53137 | 0.9717          | 0.5945   |
| 1.2475        | 40.0  | 54500 | 0.9995          | 0.5855   |
| 1.2371        | 41.0  | 55862 | 0.9861          | 0.5935   |
| 1.2561        | 42.0  | 57225 | 0.9856          | 0.5958   |
| 1.2069        | 43.0  | 58587 | 0.9913          | 0.5892   |
| 1.2188        | 44.0  | 59950 | 0.9902          | 0.5950   |
| 1.1732        | 45.0  | 61312 | 0.9892          | 0.5949   |
| 1.1705        | 46.0  | 62675 | 0.9991          | 0.5914   |
| 1.18          | 47.0  | 64037 | 0.9952          | 0.5925   |
| 1.2353        | 48.0  | 65400 | 0.9999          | 0.5933   |
| 1.2057        | 49.0  | 66762 | 1.0001          | 0.5920   |
| 1.1833        | 49.98 | 68100 | 1.0009          | 0.5928   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cu117
- Datasets 2.17.0
- Tokenizers 0.15.2