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---
license: other
base_model: neuralhaven/KDRSSC_TinyViT2MobileViT-xx-small
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: KDRSSC_TinyViT2MobileViT-xx-small-RESISC45_01
results: []
---
<!-- 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. -->
# KDRSSC_TinyViT2MobileViT-xx-small-RESISC45_01
This model is a fine-tuned version of [neuralhaven/KDRSSC_TinyViT2MobileViT-xx-small](https://huggingface.co./neuralhaven/KDRSSC_TinyViT2MobileViT-xx-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5369
- Accuracy: 0.8510
- Precision: 0.8555
- Recall: 0.8522
- F1: 0.8521
## 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: 0.0005
- train_batch_size: 256
- eval_batch_size: 256
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.1561 | 1.0 | 20 | 0.8622 | 0.7856 | 0.8025 | 0.7860 | 0.7842 |
| 0.9463 | 2.0 | 40 | 0.7009 | 0.8127 | 0.8247 | 0.8136 | 0.8142 |
| 0.7867 | 3.0 | 60 | 0.7666 | 0.7817 | 0.8076 | 0.7824 | 0.7819 |
| 0.7504 | 4.0 | 80 | 0.6580 | 0.8203 | 0.8240 | 0.8214 | 0.8194 |
| 0.7147 | 5.0 | 100 | 0.6410 | 0.8208 | 0.8348 | 0.8204 | 0.8221 |
| 0.6715 | 6.0 | 120 | 0.5923 | 0.8343 | 0.8390 | 0.8360 | 0.8356 |
| 0.6114 | 7.0 | 140 | 0.5965 | 0.8321 | 0.8415 | 0.8338 | 0.8330 |
| 0.6041 | 8.0 | 160 | 0.5625 | 0.8440 | 0.8522 | 0.8448 | 0.8456 |
| 0.5449 | 9.0 | 180 | 0.5466 | 0.8457 | 0.8508 | 0.8470 | 0.8472 |
| 0.5607 | 10.0 | 200 | 0.5369 | 0.8510 | 0.8555 | 0.8522 | 0.8521 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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