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layoutlmv3_perioli
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: 0.0371
- Precision: 0.9765
- Recall: 0.9614
- F1: 0.9689
- Accuracy: 0.9954
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: 500
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 2.94 | 50 | 0.1606 | 0.8352 | 0.8417 | 0.8385 | 0.9782 |
| No log | 5.88 | 100 | 0.0396 | 0.9565 | 0.9344 | 0.9453 | 0.9927 |
| No log | 8.82 | 150 | 0.0316 | 0.9608 | 0.9459 | 0.9533 | 0.9934 |
| No log | 11.76 | 200 | 0.0356 | 0.9881 | 0.9653 | 0.9766 | 0.9960 |
| No log | 14.71 | 250 | 0.0230 | 0.9882 | 0.9691 | 0.9786 | 0.9960 |
| No log | 17.65 | 300 | 0.0274 | 0.9881 | 0.9653 | 0.9766 | 0.9960 |
| No log | 20.59 | 350 | 0.0341 | 0.9881 | 0.9653 | 0.9766 | 0.9960 |
| No log | 23.53 | 400 | 0.0355 | 0.9765 | 0.9614 | 0.9689 | 0.9954 |
| No log | 26.47 | 450 | 0.0373 | 0.9765 | 0.9614 | 0.9689 | 0.9954 |
| 0.0774 | 29.41 | 500 | 0.0371 | 0.9765 | 0.9614 | 0.9689 | 0.9954 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.2.2
- Tokenizers 0.13.2
