transformers safetensors swin image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/swin-base-patch4-window7-224-in22k license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: microsoft/swin-base-patch4-window7-224-in22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: swin-base-patch4-window7-224-in22k
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.976218332192814
---

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# swin-base-patch4-window7-224-in22k

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224-in22k](https://huggingface.co/microsoft/swin-base-patch4-window7-224-in22k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0117
- F1: 0.9762

## 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 | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0575        | 0.99  | 50   | 0.0560          | 0.9257 |
| 0.0561        | 2.0   | 101  | 0.0359          | 0.9475 |
| 0.027         | 2.99  | 151  | 0.0212          | 0.9643 |
| 0.0236        | 4.0   | 202  | 0.0145          | 0.9737 |
| 0.0256        | 4.99  | 252  | 0.0269          | 0.9503 |
| 0.0226        | 6.0   | 303  | 0.0123          | 0.9762 |
| 0.0265        | 6.99  | 353  | 0.0135          | 0.9731 |
| 0.0168        | 8.0   | 404  | 0.0098          | 0.9824 |
| 0.0074        | 8.99  | 454  | 0.0172          | 0.9700 |
| 0.0125        | 9.9   | 500  | 0.0117          | 0.9762 |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1+cu102
- Datasets 2.16.1
- Tokenizers 0.15.1
