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layoutlmv3-funsd-keyvalue-extraction
Razgulyaistan/layoutlmv3-funsd-keyvalue-extraction
layoutlmv3-funsd-keyvalue-extraction is a machine learning model from Razgulyaistan. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as cc-by-nc-sa-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- cc-by-nc-sa-4.0
- Access
- Public
- Created
- Nov 2, 2025
- Updated
- Nov 2, 2025
- SHA
- 73a5d431
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. -->
layoutlmv3-funsd-keyvalue-extraction
This model is a fine-tuned version of microsoft/layoutlmv3-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.1346
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- 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_ratio: 0.1
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.3272 | 1.0 | 10 | 6.2929 |
| 6.2117 | 2.0 | 20 | 6.1684 |
| 6.083 | 3.0 | 30 | 5.9776 |
| 5.9712 | 4.0 | 40 | 5.7739 |
| 5.7704 | 5.0 | 50 | 5.6123 |
| 5.597 | 6.0 | 60 | 5.4913 |
| 5.4805 | 7.0 | 70 | 5.4021 |
| 5.548 | 8.0 | 80 | 5.3383 |
| 5.4142 | 9.0 | 90 | 5.2978 |
| 5.163 | 10.0 | 100 | 5.2663 |
| 5.161 | 11.0 | 110 | 5.2438 |
| 5.2217 | 12.0 | 120 | 5.2210 |
| 5.2866 | 13.0 | 130 | 5.2048 |
| 5.1409 | 14.0 | 140 | 5.1926 |
| 5.1753 | 15.0 | 150 | 5.1884 |
| 5.0544 | 16.0 | 160 | 5.1815 |
| 5.1672 | 17.0 | 170 | 5.1789 |
| 5.0112 | 18.0 | 180 | 5.1745 |
| 5.1808 | 19.0 | 190 | 5.1683 |
| 4.9891 | 20.0 | 200 | 5.1588 |
| 4.8935 | 21.0 | 210 | 5.1518 |
| 5.1338 | 22.0 | 220 | 5.1462 |
| 5.1518 | 23.0 | 230 | 5.1422 |
| 5.0453 | 24.0 | 240 | 5.1391 |
| 5.0792 | 25.0 | 250 | 5.1357 |
| 4.9074 | 26.0 | 260 | 5.1357 |
| 5.1327 | 27.0 | 270 | 5.1354 |
| 4.9889 | 28.0 | 280 | 5.1349 |
| 5.1229 | 29.0 | 290 | 5.1347 |
| 5.0974 | 30.0 | 300 | 5.1346 |
Framework versions
- PEFT 0.17.1
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.3.0
- Tokenizers 0.22.1
- Library
- peft
- License
- cc-by-nc-sa-4.0
- Created
- Nov 2, 2025
- Updated
- Nov 2, 2025