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# swin-tiny-patch4-window7-224-finetuned-aiornot-step

This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1075
- Accuracy: 0.9613
- F1: 0.9606
- Log Loss: 1.3937

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 10
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Log Loss |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|
| 0.5919        | 0.17  | 10   | 0.3100          | 0.8722   | 0.8663 | 4.6071   |
| 0.3175        | 0.34  | 20   | 0.2757          | 0.8861   | 0.8793 | 4.1038   |
| 0.2445        | 0.52  | 30   | 0.2021          | 0.9130   | 0.9092 | 3.1359   |
| 0.2117        | 0.69  | 40   | 0.1510          | 0.9377   | 0.9360 | 2.2455   |
| 0.2062        | 0.86  | 50   | 0.1535          | 0.9334   | 0.9311 | 2.4003   |
| 0.1815        | 1.03  | 60   | 0.1493          | 0.9382   | 0.9361 | 2.2261   |
| 0.1458        | 1.2   | 70   | 0.2196          | 0.9135   | 0.9089 | 3.1166   |
| 0.1507        | 1.37  | 80   | 0.1826          | 0.9243   | 0.9207 | 2.7294   |
| 0.1389        | 1.55  | 90   | 0.1396          | 0.9377   | 0.9356 | 2.2455   |
| 0.1331        | 1.72  | 100  | 0.2182          | 0.9125   | 0.9077 | 3.1553   |
| 0.1458        | 1.89  | 110  | 0.2661          | 0.9033   | 0.8978 | 3.4843   |
| 0.147         | 2.06  | 120  | 0.1068          | 0.9597   | 0.9588 | 1.4518   |
| 0.119         | 2.23  | 130  | 0.1284          | 0.9501   | 0.9484 | 1.8002   |
| 0.1045        | 2.4   | 140  | 0.1802          | 0.9291   | 0.9259 | 2.5552   |
| 0.1115        | 2.58  | 150  | 0.1434          | 0.9441   | 0.9420 | 2.0132   |
| 0.1108        | 2.75  | 160  | 0.1365          | 0.9441   | 0.9421 | 2.0132   |
| 0.1044        | 2.92  | 170  | 0.1488          | 0.9398   | 0.9375 | 2.1680   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3

no_ai ai