---
library_name: transformers
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
model-index:
- name: donut_checkpoints
  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. -->

# donut_checkpoints

This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7296

## 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: 2e-05
- train_batch_size: 2
- 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: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.0573        | 1.0   | 250  | 1.4718          |
| 0.6312        | 2.0   | 500  | 0.7169          |
| 0.2924        | 3.0   | 750  | 0.6494          |
| 0.1544        | 4.0   | 1000 | 0.6331          |
| 0.0682        | 5.0   | 1250 | 0.7624          |
| 0.0562        | 6.0   | 1500 | 0.7330          |
| 0.027         | 7.0   | 1750 | 0.7246          |
| 0.0076        | 8.0   | 2000 | 0.6950          |
| 0.0069        | 9.0   | 2250 | 0.7208          |
| 0.008         | 10.0  | 2500 | 0.7296          |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1