Downloads · 30 days
9
6% of all-time downloads
donut-invoice-finetuned
Sagarjha456/donut-invoice-finetuned
donut-invoice-finetuned is a image-text-to-text model from Sagarjha456. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
152
Public
Parameters
202M
8.1 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors810 MB · 99%
Parameter types
How the weights are stored.
F32202M · 100%
Try a prompt
Base models
Model card
From the Hugging Face model README
<!-- 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-invoice-finetuned
This model is a fine-tuned version of naver-clova-ix/donut-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5164
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 13.2058 | 1.0754 | 200 | 2.5141 |
| 6.0431 | 2.1507 | 400 | 1.3901 |
| 3.4887 | 3.2261 | 600 | 0.8637 |
| 2.0985 | 4.3015 | 800 | 0.6567 |
| 1.7233 | 5.3769 | 1000 | 0.5819 |
| 1.4555 | 6.4522 | 1200 | 0.5530 |
| 1.2787 | 7.5276 | 1400 | 0.5295 |
| 1.1393 | 8.6030 | 1600 | 0.5212 |
| 0.9891 | 9.6783 | 1800 | 0.5171 |
| 1.0770 | 10.0 | 1860 | 0.5164 |
Framework versions
- Transformers 5.10.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- License
- mit
- Created
- Jun 10, 2026
- Updated
- Jun 10, 2026