test
This model is a fine-tuned version of microsoft/layoutlmv3-base on the format_dataset dataset. It achieves the following results on the evaluation set:
- Loss: 0.0089
- Precision: 0.8870
- Recall: 0.9025
- F1: 0.8947
- Accuracy: 0.9977
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: 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 | 0.62 | 100 | 0.0405 | 0.0 | 0.0 | 0.0 | 0.9877 |
No log | 1.25 | 200 | 0.0170 | 0.7538 | 0.735 | 0.7443 | 0.9949 |
No log | 1.88 | 300 | 0.0131 | 0.7261 | 0.875 | 0.7937 | 0.9956 |
No log | 2.5 | 400 | 0.0123 | 0.7692 | 0.85 | 0.8076 | 0.9959 |
0.0271 | 3.12 | 500 | 0.0105 | 0.8098 | 0.905 | 0.8548 | 0.9968 |
0.0271 | 3.75 | 600 | 0.0106 | 0.8460 | 0.8925 | 0.8686 | 0.9972 |
0.0271 | 4.38 | 700 | 0.0086 | 0.8504 | 0.895 | 0.8721 | 0.9973 |
0.0271 | 5.0 | 800 | 0.0109 | 0.8871 | 0.845 | 0.8656 | 0.9972 |
0.0271 | 5.62 | 900 | 0.0085 | 0.8883 | 0.895 | 0.8917 | 0.9977 |
0.0042 | 6.25 | 1000 | 0.0089 | 0.8870 | 0.9025 | 0.8947 | 0.9977 |
Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
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Base model
microsoft/layoutlmv3-baseEvaluation results
- Precision on format_datasettest set self-reported0.887
- Recall on format_datasettest set self-reported0.902
- F1 on format_datasettest set self-reported0.895
- Accuracy on format_datasettest set self-reported0.998