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
- Downloads last month
- 9
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
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