|
--- |
|
license: apache-2.0 |
|
base_model: facebook/convnextv2-base-22k-224 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: convnextv2-base-22k-224-finetuned-eurosat-2 |
|
results: |
|
- task: |
|
name: Image Classification |
|
type: image-classification |
|
dataset: |
|
name: imagefolder |
|
type: imagefolder |
|
config: default |
|
split: train |
|
args: default |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.903954802259887 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# convnextv2-base-22k-224-finetuned-eurosat-2 |
|
|
|
This model is a fine-tuned version of [facebook/convnextv2-base-22k-224](https://huggingface.co/facebook/convnextv2-base-22k-224) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.3816 |
|
- Accuracy: 0.9040 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 16 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.5227 | 1.0 | 99 | 0.5333 | 0.7797 | |
|
| 0.4248 | 1.99 | 198 | 0.4145 | 0.8531 | |
|
| 0.2998 | 2.99 | 297 | 0.3307 | 0.8757 | |
|
| 0.1704 | 4.0 | 397 | 0.2664 | 0.8927 | |
|
| 0.0684 | 5.0 | 496 | 0.4353 | 0.8701 | |
|
| 0.1546 | 5.99 | 595 | 0.3920 | 0.8870 | |
|
| 0.0593 | 6.99 | 694 | 0.3801 | 0.9096 | |
|
| 0.0745 | 8.0 | 794 | 0.4030 | 0.8983 | |
|
| 0.0877 | 9.0 | 893 | 0.3846 | 0.9040 | |
|
| 0.09 | 9.97 | 990 | 0.3816 | 0.9040 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.2.0+cu118 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.2 |
|
|
