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test
This model is a fine-tuned version of microsoft/layoutlmv3-base on the funsd-layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6509
- Precision: 0.8926
- Recall: 0.9165
- F1: 0.9044
- Accuracy: 0.8601
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: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.33 | 100 | 0.7445 | 0.7475 | 0.7869 | 0.7667 | 0.7630 |
| No log | 2.67 | 200 | 0.5447 | 0.8075 | 0.8793 | 0.8419 | 0.8194 |
| No log | 4.0 | 300 | 0.5183 | 0.8425 | 0.8957 | 0.8683 | 0.8418 |
| No log | 5.33 | 400 | 0.5603 | 0.8281 | 0.8952 | 0.8603 | 0.8307 |
| 0.5735 | 6.67 | 500 | 0.5571 | 0.8535 | 0.9001 | 0.8762 | 0.8376 |
| 0.5735 | 8.0 | 600 | 0.5647 | 0.8824 | 0.9096 | 0.8958 | 0.8536 |
| 0.5735 | 9.33 | 700 | 0.5896 | 0.8802 | 0.9121 | 0.8958 | 0.8547 |
| 0.5735 | 10.67 | 800 | 0.6298 | 0.8935 | 0.9165 | 0.9049 | 0.8587 |
| 0.5735 | 12.0 | 900 | 0.6280 | 0.8965 | 0.9210 | 0.9086 | 0.8615 |
| 0.1395 | 13.33 | 1000 | 0.6509 | 0.8926 | 0.9165 | 0.9044 | 0.8601 |
Framework versions
- Transformers 4.34.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
