metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
base_model: facebook/convnext-tiny-224
model-index:
  - name: convnext-tiny-224-finetuned-eurosat-albumentations
    results:
      - task:
          type: image-classification
          name: Image Classification
        dataset:
          name: image_folder
          type: image_folder
          args: default
        metrics:
          - type: accuracy
            value: 0.9748148148148148
            name: Accuracy

convnext-tiny-224-finetuned-eurosat-albumentations

This model is a fine-tuned version of facebook/convnext-tiny-224 on the image_folder dataset. It achieves the following results on the evaluation set:

Loss: 0.0727
Accuracy: 0.9748

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.141	1.0	190	0.1496	0.9544
0.0736	2.0	380	0.0958	0.9719
0.0568	3.0	570	0.0727	0.9748

Framework versions

Transformers 4.18.0
Pytorch 1.10.0+cu111
Datasets 2.0.0
Tokenizers 0.11.6