layoutlmv3-finetuned-invoice
This model is a fine-tuned version of microsoft/layoutlmv3-base on the generated dataset. It achieves the following results on the evaluation set:
- Loss: 0.0013
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
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: 1
- eval_batch_size: 1
- 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 |
---|---|---|---|---|---|---|---|
0.144 | 5.0 | 500 | 0.0124 | 0.972 | 0.9858 | 0.9789 | 0.9971 |
0.0081 | 10.0 | 1000 | 0.0042 | 0.9960 | 0.9980 | 0.9970 | 0.9996 |
0.0034 | 15.0 | 1500 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 |
0.0023 | 20.0 | 2000 | 0.0018 | 0.9980 | 1.0 | 0.9990 | 0.9998 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- Downloads last month
- 62
Inference Providers
NEW
This model is not currently available via any of the supported Inference Providers.
Model tree for smitbutle/layoutlmv3-finetuned-invoice
Base model
microsoft/layoutlmv3-baseEvaluation results
- Precision on generatedtest set self-reported1.000
- Recall on generatedtest set self-reported1.000
- F1 on generatedtest set self-reported1.000
- Accuracy on generatedtest set self-reported1.000