Downloads · 30 days
997
4% of all-time downloads
layoutlmv3-finetuned-cord
nielsr/layoutlmv3-finetuned-cord
layoutlmv3-finetuned-cord is a token classification model from nielsr. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
22.7K
Public
Parameters
126M
2.5 GB on disk
Likes
14
Public
Repo makeup
Click a slice to open those files.
.bin504 MB · 50%
Parameter types
How the weights are stored.
F32126M · 100%
Try a prompt
Base models
Datasets
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-finetuned-cord
This model is a fine-tuned version of microsoft/layoutlmv3-base on the CORD dataset. It achieves the following results on the evaluation set:
- Loss: 0.1845
- Precision: 0.9620
- Recall: 0.9656
- F1: 0.9638
- Accuracy: 0.9682
The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 2.0 | 100 | 0.5257 | 0.8223 | 0.8555 | 0.8386 | 0.8710 |
| No log | 4.0 | 200 | 0.3200 | 0.9118 | 0.9281 | 0.9199 | 0.9317 |
| No log | 6.0 | 300 | 0.2449 | 0.9298 | 0.9424 | 0.9361 | 0.9465 |
| No log | 8.0 | 400 | 0.1923 | 0.9472 | 0.9536 | 0.9504 | 0.9597 |
| 0.4328 | 10.0 | 500 | 0.1857 | 0.9591 | 0.9656 | 0.9623 | 0.9682 |
| 0.4328 | 12.0 | 600 | 0.2073 | 0.9597 | 0.9618 | 0.9607 | 0.9656 |
| 0.4328 | 14.0 | 700 | 0.1804 | 0.9634 | 0.9663 | 0.9649 | 0.9703 |
| 0.4328 | 16.0 | 800 | 0.1882 | 0.9634 | 0.9648 | 0.9641 | 0.9665 |
| 0.4328 | 18.0 | 900 | 0.1800 | 0.9619 | 0.9648 | 0.9634 | 0.9677 |
| 0.0318 | 20.0 | 1000 | 0.1845 | 0.9620 | 0.9656 | 0.9638 | 0.9682 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6
- Task
- Token Classification
- Library
- transformers
- Type
- layoutlmv3
- Created
- May 2, 2022
- Updated
- Sep 19, 2023