layoutlmv3-finetuned-cord_100
This model is a fine-tuned version of microsoft/layoutlmv3-base on the cord-layoutlmv3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2123
- Precision: 0.9458
- Recall: 0.9543
- F1: 0.9501
- Accuracy: 0.9597
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: 5
- eval_batch_size: 5
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 2500
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.56 | 250 | 1.0095 | 0.7120 | 0.7754 | 0.7424 | 0.7946 |
1.3738 | 3.12 | 500 | 0.5732 | 0.8473 | 0.8683 | 0.8577 | 0.8714 |
1.3738 | 4.69 | 750 | 0.3840 | 0.8893 | 0.9079 | 0.8985 | 0.9181 |
0.4085 | 6.25 | 1000 | 0.2933 | 0.9181 | 0.9319 | 0.9250 | 0.9376 |
0.4085 | 7.81 | 1250 | 0.2704 | 0.9197 | 0.9349 | 0.9272 | 0.9444 |
0.2239 | 9.38 | 1500 | 0.2504 | 0.9369 | 0.9454 | 0.9411 | 0.9508 |
0.2239 | 10.94 | 1750 | 0.2375 | 0.9288 | 0.9379 | 0.9333 | 0.9465 |
0.1544 | 12.5 | 2000 | 0.2326 | 0.9423 | 0.9528 | 0.9475 | 0.9576 |
0.1544 | 14.06 | 2250 | 0.2147 | 0.9530 | 0.9566 | 0.9548 | 0.9610 |
0.1231 | 15.62 | 2500 | 0.2123 | 0.9458 | 0.9543 | 0.9501 | 0.9597 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
microsoft/layoutlmv3-baseEvaluation results
- Precision on cord-layoutlmv3test set self-reported0.946
- Recall on cord-layoutlmv3test set self-reported0.954
- F1 on cord-layoutlmv3test set self-reported0.950
- Accuracy on cord-layoutlmv3test set self-reported0.960