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nexon_jan_2023
This model is a fine-tuned version of microsoft/layoutlmv3-base on the sroie dataset. It achieves the following results on the evaluation set:
- Loss: 0.0380
- Precision: 0.9756
- Recall: 0.9302
- F1: 0.9524
- 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: 1500
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 16.67 | 100 | 0.1998 | 0.6286 | 0.5116 | 0.5641 | 0.9571 |
| No log | 33.33 | 200 | 0.0616 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| No log | 50.0 | 300 | 0.0439 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| No log | 66.67 | 400 | 0.0404 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.1151 | 83.33 | 500 | 0.0389 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.1151 | 100.0 | 600 | 0.0380 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.1151 | 116.67 | 700 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.1151 | 133.33 | 800 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.1151 | 150.0 | 900 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.009 | 166.67 | 1000 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.009 | 183.33 | 1100 | 0.0378 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.009 | 200.0 | 1200 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.009 | 216.67 | 1300 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.009 | 233.33 | 1400 | 0.0379 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
| 0.0064 | 250.0 | 1500 | 0.0380 | 0.9756 | 0.9302 | 0.9524 | 0.9971 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2
