
<!-- 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-base-patch4-window7-224-finetuned-barkley

This model is a fine-tuned version of [microsoft/swin-base-patch4-window7-224](https://huggingface.co/microsoft/swin-base-patch4-window7-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0126
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
- Top1 Accuracy: 1.0
- Error Rate: 0.0

## 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 1.6386        | 0.9474 | 9    | 1.2206          | 0.7199    | 0.6842 | 0.6848 | 0.6800   | 0.6842        | 0.3200     |
| 0.7786        | 2.0    | 19   | 0.3487          | 0.9484    | 0.9474 | 0.9467 | 0.9497   | 0.9474        | 0.0503     |
| 0.1763        | 2.9474 | 28   | 0.0609          | 0.9937    | 0.9934 | 0.9934 | 0.9944   | 0.9934        | 0.0056     |
| 0.0472        | 4.0    | 38   | 0.0318          | 0.9871    | 0.9868 | 0.9868 | 0.9878   | 0.9868        | 0.0122     |
| 0.0316        | 4.9474 | 47   | 0.0126          | 1.0       | 1.0    | 1.0    | 1.0      | 1.0           | 0.0        |
| 0.0171        | 6.0    | 57   | 0.0392          | 0.9875    | 0.9868 | 0.9868 | 0.9867   | 0.9868        | 0.0133     |
| 0.0152        | 6.9474 | 66   | 0.0042          | 1.0       | 1.0    | 1.0    | 1.0      | 1.0           | 0.0        |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1

iinstia bijuga mangifera indica pterocarpus indicus roystonea regia tabebuia