metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: convnextv2-large-1k-224-finetuned-eurosat-50
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: Augmented-Final
split: train
args: Augmented-Final
metrics:
- name: Accuracy
type: accuracy
value: 0.959917780061665
convnextv2-large-1k-224-finetuned-eurosat-50
This model is a fine-tuned version of facebook/convnextv2-large-1k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1615
- Accuracy: 0.9599
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.9
- num_epochs: 12
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.9003 | 1.0 | 122 | 1.8892 | 0.3587 |
| 1.6055 | 2.0 | 244 | 1.5936 | 0.5766 |
| 1.2982 | 3.0 | 366 | 1.2568 | 0.6639 |
| 1.0273 | 4.0 | 488 | 0.9558 | 0.7431 |
| 0.7863 | 5.0 | 610 | 0.7440 | 0.7965 |
| 0.8142 | 6.0 | 732 | 0.6206 | 0.8304 |
| 0.6118 | 7.0 | 854 | 0.4672 | 0.8684 |
| 0.4776 | 8.0 | 976 | 0.3756 | 0.9075 |
| 0.4176 | 9.0 | 1098 | 0.3065 | 0.9301 |
| 0.282 | 10.0 | 1220 | 0.2586 | 0.9404 |
| 0.306 | 11.0 | 1342 | 0.2098 | 0.9476 |
| 0.2006 | 12.0 | 1464 | 0.1615 | 0.9599 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3