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---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut_marriage_RT_539-135_301123
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_marriage_RT_539-135_301123
This model is a fine-tuned version of [naver-clova-ix/donut-base](https://huggingface.co/naver-clova-ix/donut-base) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1088
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1504 | 1.0 | 270 | 0.5023 |
| 0.1444 | 2.0 | 540 | 0.2738 |
| 0.2701 | 3.0 | 810 | 0.1902 |
| 0.3624 | 4.0 | 1080 | 0.1666 |
| 0.1274 | 5.0 | 1350 | 0.1542 |
| 0.0369 | 6.0 | 1620 | 0.1537 |
| 0.0615 | 7.0 | 1890 | 0.1402 |
| 0.0271 | 8.0 | 2160 | 0.1293 |
| 0.0142 | 9.0 | 2430 | 0.1262 |
| 0.2481 | 10.0 | 2700 | 0.1255 |
| 0.002 | 11.0 | 2970 | 0.1260 |
| 0.0098 | 12.0 | 3240 | 0.1244 |
| 0.0045 | 13.0 | 3510 | 0.1214 |
| 0.0001 | 14.0 | 3780 | 0.1278 |
| 0.0011 | 15.0 | 4050 | 0.1227 |
| 0.0006 | 16.0 | 4320 | 0.1226 |
| 0.0003 | 17.0 | 4590 | 0.1212 |
| 0.0022 | 18.0 | 4860 | 0.1170 |
| 0.0002 | 19.0 | 5130 | 0.1141 |
| 0.0002 | 20.0 | 5400 | 0.1176 |
| 0.0004 | 21.0 | 5670 | 0.1142 |
| 0.0001 | 22.0 | 5940 | 0.1096 |
| 0.0003 | 23.0 | 6210 | 0.1090 |
| 0.0002 | 24.0 | 6480 | 0.1092 |
| 0.0001 | 25.0 | 6750 | 0.1088 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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