layoutlmv3-finetuned-funsd
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
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: 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
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Dataset used to train Narsil/layoutlmv3-finetuned-funsd
Evaluation results
- Precision on nielsr/funsd-layoutlmv3self-reported0.903
- Recall on nielsr/funsd-layoutlmv3self-reported0.913
- F1 on nielsr/funsd-layoutlmv3self-reported0.908
- Accuracy on nielsr/funsd-layoutlmv3self-reported0.833