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swin-original-10

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swin-original-10
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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-original-10
  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: 0.9916476841305999
---

<!-- 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-original-10

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: 0.0443
- Accuracy: 0.9916

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 5.6259        | 1.0   | 247  | 3.3200          | 0.3994   |
| 1.9734        | 2.0   | 494  | 0.5108          | 0.9370   |
| 0.6166        | 3.0   | 741  | 0.2288          | 0.9749   |
| 0.4348        | 4.0   | 988  | 0.1149          | 0.9858   |
| 0.2823        | 5.0   | 1235 | 0.0760          | 0.9899   |
| 0.2351        | 6.0   | 1482 | 0.0618          | 0.9906   |
| 0.1889        | 7.0   | 1729 | 0.0550          | 0.9894   |
| 0.1681        | 8.0   | 1976 | 0.0505          | 0.9901   |
| 0.144         | 9.0   | 2223 | 0.0446          | 0.9919   |
| 0.1248        | 10.0  | 2470 | 0.0443          | 0.9916   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 3.0.0
- Tokenizers 0.15.2