deit-ena24 / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/deit-base-distilled-patch16-224
tags:
  - image-classification
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: deit-ena24
    results: []

deit-ena24

This model is a fine-tuned version of facebook/deit-base-distilled-patch16-224 on the ena24 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0870
  • Accuracy: 0.9794

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: 0.0002
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Accuracy
1.2994 0.1302 100 1.0314 0.7092
0.8789 0.2604 200 0.6169 0.8328
0.4592 0.3906 300 0.5234 0.8298
0.6806 0.5208 400 0.5431 0.8489
0.4878 0.6510 500 0.3905 0.8855
0.4643 0.7812 600 0.3281 0.9092
0.3765 0.9115 700 0.2398 0.9290
0.1379 1.0417 800 0.1861 0.9412
0.1422 1.1719 900 0.1657 0.9527
0.2655 1.3021 1000 0.1526 0.9557
0.0304 1.4323 1100 0.1578 0.9634
0.072 1.5625 1200 0.1418 0.9679
0.2936 1.6927 1300 0.1003 0.9771
0.0333 1.8229 1400 0.0935 0.9794
0.0844 1.9531 1500 0.0870 0.9794

Framework versions

  • Transformers 4.51.1
  • Pytorch 2.6.0+cu124
  • Datasets 3.5.0
  • Tokenizers 0.21.1