donut-base-sroie / README.md
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---
license: mit
base_model: naver-clova-ix/donut-base
tags:
- generated_from_trainer
datasets:
- imagefolder
model-index:
- name: donut-base-sroie
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-base-sroie
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: 1.1461
## 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.8948 | 1.0 | 45 | 5.7211 |
| 3.2707 | 2.0 | 90 | 2.8623 |
| 2.1611 | 3.0 | 135 | 1.7889 |
| 1.3332 | 4.0 | 180 | 1.4790 |
| 0.6255 | 5.0 | 225 | 1.3553 |
| 1.2248 | 6.0 | 270 | 1.2488 |
| 0.9245 | 7.0 | 315 | 1.1895 |
| 0.4144 | 8.0 | 360 | 1.2128 |
| 0.4087 | 9.0 | 405 | 1.1811 |
| 0.4926 | 10.0 | 450 | 1.1461 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1