---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# deit-ena24

This model is a fine-tuned version of [facebook/deit-base-distilled-patch16-224](https://huggingface.co/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