---
license: apache-2.0
base_model: neuralhaven/KDRSSC_ViT2TinyViT
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_ViT2TinyViT-RESISC45_FT
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# KDRSSC_ViT2TinyViT-RESISC45_FT

This model is a fine-tuned version of [neuralhaven/KDRSSC_ViT2TinyViT](https://huggingface.co/neuralhaven/KDRSSC_ViT2TinyViT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2192
- Accuracy: 0.9403
- Precision: 0.9412
- Recall: 0.9410
- F1: 0.9406

## 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: 512
- eval_batch_size: 512
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 3.1125        | 1.0   | 37   | 0.9645          | 0.911    | 0.9167    | 0.9076 | 0.9069 |
| 0.6036        | 2.0   | 74   | 0.2854          | 0.938    | 0.9387    | 0.9394 | 0.9370 |
| 0.4344        | 3.0   | 111  | 0.2315          | 0.942    | 0.9412    | 0.9422 | 0.9395 |
| 0.3572        | 4.0   | 148  | 0.1993          | 0.948    | 0.9480    | 0.9487 | 0.9464 |
| 0.3086        | 5.0   | 185  | 0.2025          | 0.94     | 0.9405    | 0.9391 | 0.9372 |
| 0.2906        | 6.0   | 222  | 0.1979          | 0.939    | 0.9394    | 0.9381 | 0.9358 |
| 0.2567        | 7.0   | 259  | 0.1814          | 0.943    | 0.9427    | 0.9440 | 0.9413 |
| 0.2785        | 8.0   | 296  | 0.1563          | 0.948    | 0.9470    | 0.9484 | 0.9464 |
| 0.2462        | 9.0   | 333  | 0.1509          | 0.951    | 0.9508    | 0.9524 | 0.9501 |
| 0.245         | 10.0  | 370  | 0.1489          | 0.949    | 0.9475    | 0.9492 | 0.9468 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1