metadata
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned-eurosat-albumentations
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: 0.9833333333333333
convnext-tiny-224-finetuned-eurosat-albumentations
This model is a fine-tuned version of facebook/convnext-tiny-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0546
- Accuracy: 0.9833
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: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1696 | 1.0 | 190 | 0.1738 | 0.9559 |
| 0.0887 | 2.0 | 380 | 0.0837 | 0.9770 |
| 0.0483 | 3.0 | 570 | 0.0790 | 0.9774 |
| 0.0387 | 4.0 | 760 | 0.0701 | 0.9793 |
| 0.0454 | 5.0 | 950 | 0.0595 | 0.9826 |
| 0.0215 | 6.0 | 1140 | 0.0574 | 0.9819 |
| 0.0281 | 7.0 | 1330 | 0.0546 | 0.9833 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.0