layoutlmv3-finetuned-registros_v2
This model is a fine-tuned version of microsoft/layoutlmv3-base on the data_registros_layoutv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1473
- Precision: 0.8606
- Recall: 0.9374
- F1: 0.8974
- Accuracy: 0.9817
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-06
- train_batch_size: 4
- eval_batch_size: 4
- 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 | 10.87 | 250 | 0.4204 | 0.4257 | 0.4351 | 0.4303 | 0.9104 |
0.6077 | 21.74 | 500 | 0.2246 | 0.7957 | 0.8654 | 0.8291 | 0.9683 |
0.6077 | 32.61 | 750 | 0.1636 | 0.8438 | 0.9218 | 0.8811 | 0.9765 |
0.1638 | 43.48 | 1000 | 0.1473 | 0.8606 | 0.9374 | 0.8974 | 0.9817 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
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Evaluation results
- Precision on data_registros_layoutv3test set self-reported0.861
- Recall on data_registros_layoutv3test set self-reported0.937
- F1 on data_registros_layoutv3test set self-reported0.897
- Accuracy on data_registros_layoutv3test set self-reported0.982