---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-fish
  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: 0.9411764705882353
---

<!-- 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-tiny-patch4-window7-224-finetuned-fish

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: 0.4264
- Accuracy: 0.9412

## 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: 75

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.8   | 1    | 1.8035          | 0.2941   |
| No log        | 1.6   | 2    | 1.7861          | 0.2941   |
| No log        | 2.4   | 3    | 1.7554          | 0.2941   |
| No log        | 4.0   | 5    | 1.6954          | 0.3529   |
| No log        | 4.8   | 6    | 1.6780          | 0.4118   |
| No log        | 5.6   | 7    | 1.6536          | 0.4118   |
| No log        | 6.4   | 8    | 1.6222          | 0.4118   |
| 1.6467        | 8.0   | 10   | 1.4682          | 0.5294   |
| 1.6467        | 8.8   | 11   | 1.3261          | 0.5294   |
| 1.6467        | 9.6   | 12   | 1.1888          | 0.5294   |
| 1.6467        | 10.4  | 13   | 1.0433          | 0.5294   |
| 1.6467        | 12.0  | 15   | 0.8212          | 0.5882   |
| 1.6467        | 12.8  | 16   | 0.7240          | 0.7059   |
| 1.6467        | 13.6  | 17   | 0.6390          | 0.8235   |
| 1.6467        | 14.4  | 18   | 0.5594          | 0.8824   |
| 0.782         | 16.0  | 20   | 0.4647          | 0.8235   |
| 0.782         | 16.8  | 21   | 0.4264          | 0.9412   |
| 0.782         | 17.6  | 22   | 0.3983          | 0.9412   |
| 0.782         | 18.4  | 23   | 0.3760          | 0.9412   |
| 0.782         | 20.0  | 25   | 0.3751          | 0.8824   |
| 0.782         | 20.8  | 26   | 0.3553          | 0.8824   |
| 0.782         | 21.6  | 27   | 0.3161          | 0.8824   |
| 0.782         | 22.4  | 28   | 0.2706          | 0.9412   |
| 0.3228        | 24.0  | 30   | 0.2100          | 0.9412   |
| 0.3228        | 24.8  | 31   | 0.1885          | 0.9412   |
| 0.3228        | 25.6  | 32   | 0.1727          | 0.9412   |
| 0.3228        | 26.4  | 33   | 0.1818          | 0.9412   |
| 0.3228        | 28.0  | 35   | 0.1959          | 0.8824   |
| 0.3228        | 28.8  | 36   | 0.1889          | 0.9412   |
| 0.3228        | 29.6  | 37   | 0.1995          | 0.8824   |
| 0.3228        | 30.4  | 38   | 0.2093          | 0.8824   |
| 0.2375        | 32.0  | 40   | 0.1869          | 0.9412   |
| 0.2375        | 32.8  | 41   | 0.1648          | 0.9412   |
| 0.2375        | 33.6  | 42   | 0.1576          | 0.9412   |
| 0.2375        | 34.4  | 43   | 0.1709          | 0.9412   |
| 0.2375        | 36.0  | 45   | 0.1717          | 0.9412   |
| 0.2375        | 36.8  | 46   | 0.1783          | 0.9412   |
| 0.2375        | 37.6  | 47   | 0.1993          | 0.8824   |
| 0.2375        | 38.4  | 48   | 0.2085          | 0.8824   |
| 0.1897        | 40.0  | 50   | 0.2028          | 0.8824   |
| 0.1897        | 40.8  | 51   | 0.1704          | 0.9412   |
| 0.1897        | 41.6  | 52   | 0.1520          | 0.9412   |
| 0.1897        | 42.4  | 53   | 0.1325          | 0.9412   |
| 0.1897        | 44.0  | 55   | 0.1451          | 0.9412   |
| 0.1897        | 44.8  | 56   | 0.1664          | 0.9412   |
| 0.1897        | 45.6  | 57   | 0.1927          | 0.8824   |
| 0.1897        | 46.4  | 58   | 0.2202          | 0.8824   |
| 0.1676        | 48.0  | 60   | 0.2569          | 0.8824   |
| 0.1676        | 48.8  | 61   | 0.2748          | 0.8824   |
| 0.1676        | 49.6  | 62   | 0.2612          | 0.8824   |
| 0.1676        | 50.4  | 63   | 0.2414          | 0.8824   |
| 0.1676        | 52.0  | 65   | 0.1842          | 0.8824   |
| 0.1676        | 52.8  | 66   | 0.1597          | 0.8824   |
| 0.1676        | 53.6  | 67   | 0.1447          | 0.8824   |
| 0.1676        | 54.4  | 68   | 0.1359          | 0.9412   |
| 0.1452        | 56.0  | 70   | 0.1367          | 0.9412   |
| 0.1452        | 56.8  | 71   | 0.1402          | 0.9412   |
| 0.1452        | 57.6  | 72   | 0.1462          | 0.8824   |
| 0.1452        | 58.4  | 73   | 0.1515          | 0.8824   |
| 0.1452        | 60.0  | 75   | 0.1585          | 0.8824   |


### Framework versions

- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.15.0