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---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: resnet-18-finetuned-eurosat
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. -->
# resnet-18-finetuned-eurosat
This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5506
- Accuracy: 0.8364
## 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: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3846 | 0.99 | 20 | 0.6352 | 0.7576 |
| 0.5009 | 1.98 | 40 | 0.6439 | 0.7485 |
| 0.5625 | 2.96 | 60 | 0.5722 | 0.7909 |
| 0.4928 | 4.0 | 81 | 0.5514 | 0.7970 |
| 0.4621 | 4.99 | 101 | 0.6104 | 0.7697 |
| 0.4367 | 5.98 | 121 | 0.5734 | 0.7939 |
| 0.4238 | 6.96 | 141 | 0.5558 | 0.8 |
| 0.4011 | 8.0 | 162 | 0.5549 | 0.8030 |
| 0.4129 | 8.99 | 182 | 0.5554 | 0.8061 |
| 0.384 | 9.98 | 202 | 0.5551 | 0.8152 |
| 0.3839 | 10.96 | 222 | 0.5742 | 0.8091 |
| 0.3496 | 12.0 | 243 | 0.5518 | 0.8303 |
| 0.3482 | 12.99 | 263 | 0.5390 | 0.8303 |
| 0.357 | 13.98 | 283 | 0.5544 | 0.8182 |
| 0.3341 | 14.96 | 303 | 0.5506 | 0.8364 |
| 0.3605 | 16.0 | 324 | 0.5546 | 0.8212 |
| 0.3041 | 16.99 | 344 | 0.5597 | 0.8212 |
| 0.3364 | 17.98 | 364 | 0.5730 | 0.8091 |
| 0.2976 | 18.96 | 384 | 0.5742 | 0.8091 |
| 0.3229 | 19.75 | 400 | 0.5653 | 0.8121 |
### Framework versions
- Transformers 4.30.1
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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