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LayoutLMv3_5_entities_filtred_11
This model is a fine-tuned version of microsoft/layoutlmv3-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.2520
- Precision: 0.5
- Recall: 0.1818
- F1: 0.2667
- Accuracy: 0.7959
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: 2000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 100.0 | 100 | 1.2300 | 0.4 | 0.1818 | 0.2500 | 0.7755 |
| No log | 200.0 | 200 | 1.6008 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| No log | 300.0 | 300 | 1.7235 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| No log | 400.0 | 400 | 1.8766 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0576 | 500.0 | 500 | 1.9181 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0576 | 600.0 | 600 | 1.9628 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0576 | 700.0 | 700 | 2.0079 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0576 | 800.0 | 800 | 2.0811 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0576 | 900.0 | 900 | 2.1047 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0004 | 1000.0 | 1000 | 2.1393 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0004 | 1100.0 | 1100 | 2.1754 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0004 | 1200.0 | 1200 | 2.1824 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0004 | 1300.0 | 1300 | 2.2005 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0004 | 1400.0 | 1400 | 2.1555 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0003 | 1500.0 | 1500 | 2.2045 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0003 | 1600.0 | 1600 | 2.2249 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0003 | 1700.0 | 1700 | 2.2358 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0003 | 1800.0 | 1800 | 2.2460 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0003 | 1900.0 | 1900 | 2.2514 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
| 0.0002 | 2000.0 | 2000 | 2.2520 | 0.5 | 0.1818 | 0.2667 | 0.7959 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.13.3
