test
This model is a fine-tuned version of microsoft/layoutlmv3-base on the layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0899
- Precision: 0.9736
- Recall: 0.9752
- F1: 0.9744
- Accuracy: 0.9924
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- training_steps: 1000
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 0.5291 | 100 | 0.4956 | 0.7821 | 0.7724 | 0.7772 | 0.9413 |
No log | 1.0582 | 200 | 0.1802 | 0.9285 | 0.9247 | 0.9266 | 0.9761 |
No log | 1.5873 | 300 | 0.1465 | 0.9334 | 0.9512 | 0.9422 | 0.9841 |
No log | 2.1164 | 400 | 0.1309 | 0.9447 | 0.9611 | 0.9528 | 0.9876 |
0.3392 | 2.6455 | 500 | 0.1095 | 0.9516 | 0.9594 | 0.9555 | 0.9891 |
0.3392 | 3.1746 | 600 | 0.1022 | 0.9573 | 0.9652 | 0.9613 | 0.9915 |
0.3392 | 3.7037 | 700 | 0.1081 | 0.9573 | 0.9661 | 0.9617 | 0.9918 |
0.3392 | 4.2328 | 800 | 0.0922 | 0.9726 | 0.9694 | 0.9710 | 0.9920 |
0.3392 | 4.7619 | 900 | 0.0930 | 0.9702 | 0.9702 | 0.9702 | 0.9916 |
0.0282 | 5.2910 | 1000 | 0.0899 | 0.9736 | 0.9752 | 0.9744 | 0.9924 |
Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
microsoft/layoutlmv3-baseEvaluation results
- Precision on layoutlmv3test set self-reported0.974
- Recall on layoutlmv3test set self-reported0.975
- F1 on layoutlmv3test set self-reported0.974
- Accuracy on layoutlmv3test set self-reported0.992