layoutlmv3-finetuned-registros_100
This model was trained from scratch on the data_registros_layoutv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.0050
- Precision: 0.9968
- Recall: 0.9951
- F1: 0.9960
- Accuracy: 0.9995
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: 600
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 4.35 | 100 | 0.0106 | 0.9871 | 0.9935 | 0.9903 | 0.9991 |
No log | 8.7 | 200 | 0.0073 | 0.9984 | 0.9968 | 0.9976 | 0.9997 |
No log | 13.04 | 300 | 0.0061 | 0.9968 | 0.9968 | 0.9968 | 0.9997 |
No log | 17.39 | 400 | 0.0048 | 0.9968 | 0.9984 | 0.9976 | 0.9997 |
0.0109 | 21.74 | 500 | 0.0053 | 0.9968 | 0.9968 | 0.9968 | 0.9997 |
0.0109 | 26.09 | 600 | 0.0050 | 0.9968 | 0.9951 | 0.9960 | 0.9995 |
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-reported0.997
- Recall on data_registros_layoutv3test set self-reported0.995
- F1 on data_registros_layoutv3test set self-reported0.996
- Accuracy on data_registros_layoutv3test set self-reported1.000