đ layoutlmv3-finetuned-funsd
This model is a fine - tuned version of microsoft/layoutlmv3-base on the nielsr/funsd-layoutlmv3 dataset, achieving excellent results in token classification tasks.
đ Quick Start
This model is a fine-tuned version of microsoft/layoutlmv3-base on the nielsr/funsd-layoutlmv3 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1164
- Precision: 0.9026
- Recall: 0.913
- F1: 0.9078
- Accuracy: 0.8330
The script for training can be found here: https://github.com/huggingface/transformers/tree/main/examples/research_projects/layoutlmv3
đ Documentation
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
đ§ Technical Details
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-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 |
10.0 |
100 |
0.5238 |
0.8366 |
0.886 |
0.8606 |
0.8410 |
| No log |
20.0 |
200 |
0.6930 |
0.8751 |
0.8965 |
0.8857 |
0.8322 |
| No log |
30.0 |
300 |
0.7784 |
0.8902 |
0.908 |
0.8990 |
0.8414 |
| No log |
40.0 |
400 |
0.9056 |
0.8916 |
0.905 |
0.8983 |
0.8364 |
| 0.2429 |
50.0 |
500 |
1.0016 |
0.8954 |
0.9075 |
0.9014 |
0.8298 |
| 0.2429 |
60.0 |
600 |
1.0097 |
0.8899 |
0.897 |
0.8934 |
0.8294 |
| 0.2429 |
70.0 |
700 |
1.0722 |
0.9035 |
0.9085 |
0.9060 |
0.8315 |
| 0.2429 |
80.0 |
800 |
1.0884 |
0.8905 |
0.9105 |
0.9004 |
0.8269 |
| 0.2429 |
90.0 |
900 |
1.1292 |
0.8938 |
0.909 |
0.9013 |
0.8279 |
| 0.0098 |
100.0 |
1000 |
1.1164 |
0.9026 |
0.913 |
0.9078 |
0.8330 |
Framework versions
- Transformers 4.19.0.dev0
- Pytorch 1.11.0+cu113
- Datasets 2.0.0
- Tokenizers 0.11.6
đ License
No license information provided in the original document, so this section is skipped.
đĻ Installation
No installation steps provided in the original document, so this section is skipped.
đģ Usage Examples
No code examples provided in the original document, so this section is skipped.
đ Information Table
| Property |
Details |
| Tags |
generated_from_trainer |
| Datasets |
nielsr/funsd-layoutlmv3 |
| Pipeline Tag |
object-detection |
| Duplicated From |
nielsr/layoutlmv3-finetuned-funsd |
| Metrics |
precision, recall, f1, accuracy |
| Model Index Name |
layoutlmv3-finetuned-funsd |
| Evaluation Results - Precision |
0.9026198714780029 |
| Evaluation Results - Recall |
0.913 |
| Evaluation Results - F1 |
0.9077802634849614 |
| Evaluation Results - Accuracy |
0.8330271015158475 |
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