README.md

metadata

license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
  - generated_from_trainer
datasets:
  - image_folder
metrics:
  - accuracy
model-index:
  - name: convnextv2-tiny-1k-224-finetuned-eurosat
    results:
      - task:
          name: Image Classification
          type: image-classification
        dataset:
          name: image_folder
          type: image_folder
          config: default
          split: train
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.7512562814070352

convnextv2-tiny-1k-224-finetuned-eurosat

This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on the image_folder dataset. It achieves the following results on the evaluation set:

• Loss: 0.5454
• Accuracy: 0.7513

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: 64
• eval_batch_size: 64
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 256
• 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
0.6352	1.0	14	0.5507	0.7462
0.5508	2.0	28	0.5477	0.7487
0.5313	3.0	42	0.5454	0.7513

Framework versions

• Transformers 4.33.0
• Pytorch 2.0.0
• Datasets 2.1.0
• Tokenizers 0.13.3