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layoutlmv3-finetuned-invoice
This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset. It achieves the following results on the evaluation set:
- Loss: 0.0116
- Precision: 0.972
- Recall: 0.9858
- F1: 0.9789
- Accuracy: 0.9971
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: 875
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 2.0 | 100 | 0.0898 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 4.0 | 200 | 0.0251 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 6.0 | 300 | 0.0176 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| No log | 8.0 | 400 | 0.0148 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1241 | 10.0 | 500 | 0.0116 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
| 0.1241 | 12.0 | 600 | 0.0072 | 0.9919 | 0.9959 | 0.9939 | 0.9992 |
| 0.1241 | 14.0 | 700 | 0.0059 | 0.9960 | 0.9980 | 0.9970 | 0.9996 |
| 0.1241 | 16.0 | 800 | 0.0044 | 0.9980 | 0.9980 | 0.9980 | 0.9998 |
Framework versions
- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
