| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - sroie |
| | metrics: |
| | - precision |
| | - recall |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: test_model |
| | results: |
| | - task: |
| | name: Token Classification |
| | type: token-classification |
| | dataset: |
| | name: sroie |
| | type: sroie |
| | config: discharge |
| | split: test |
| | args: discharge |
| | metrics: |
| | - name: Precision |
| | type: precision |
| | value: 0.9343065693430657 |
| | - name: Recall |
| | type: recall |
| | value: 0.9696969696969697 |
| | - name: F1 |
| | type: f1 |
| | value: 0.9516728624535317 |
| | - name: Accuracy |
| | type: accuracy |
| | value: 0.9976019184652278 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # test_model |
| | |
| | This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on the sroie dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0114 |
| | - Precision: 0.9343 |
| | - Recall: 0.9697 |
| | - F1: 0.9517 |
| | - Accuracy: 0.9976 |
| | |
| | ## 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 | 8.33 | 100 | 0.0292 | 0.8732 | 0.9394 | 0.9051 | 0.9928 | |
| | | No log | 16.67 | 200 | 0.0110 | 0.9343 | 0.9697 | 0.9517 | 0.9976 | |
| | | No log | 25.0 | 300 | 0.0130 | 0.9209 | 0.9697 | 0.9446 | 0.9971 | |
| | | No log | 33.33 | 400 | 0.0110 | 0.9412 | 0.9697 | 0.9552 | 0.9981 | |
| | | 0.0466 | 41.67 | 500 | 0.0114 | 0.9275 | 0.9697 | 0.9481 | 0.9976 | |
| | | 0.0466 | 50.0 | 600 | 0.0117 | 0.9275 | 0.9697 | 0.9481 | 0.9976 | |
| | | 0.0466 | 58.33 | 700 | 0.0114 | 0.9275 | 0.9697 | 0.9481 | 0.9976 | |
| | | 0.0466 | 66.67 | 800 | 0.0114 | 0.9343 | 0.9697 | 0.9517 | 0.9976 | |
| | | 0.0466 | 75.0 | 900 | 0.0115 | 0.9343 | 0.9697 | 0.9517 | 0.9976 | |
| | | 0.0006 | 83.33 | 1000 | 0.0114 | 0.9343 | 0.9697 | 0.9517 | 0.9976 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.28.0 |
| | - Pytorch 2.0.0+cu118 |
| | - Datasets 2.2.2 |
| | - Tokenizers 0.13.3 |
| | |
