metadata

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
    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: 0.8418079096045198

convnextv2-base-22k-224-finetuned-eurosat

This model is a fine-tuned version of facebook/convnextv2-base-22k-224 on the imagefolder dataset. It achieves the following results on the evaluation set:

Loss: 0.4225
Accuracy: 0.8418

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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
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
0.5909	1.0	198	0.5287	0.7966
0.2224	2.0	396	0.4225	0.8418
0.1975	3.0	594	0.4207	0.8418

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu118
Datasets 2.17.0
Tokenizers 0.15.2