| | --- |
| | license: cc-by-nc-sa-4.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: layoutlmv3-base-ner |
| | results: [] |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # layoutlmv3-base-ner |
| |
|
| | This model is a fine-tuned version of [microsoft/layoutlmv3-base](https://huggingface.co/microsoft/layoutlmv3-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 1.1562 |
| | - Footer: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} |
| | - Header: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} |
| | - Able: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} |
| | - Aption: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} |
| | - Ext: {'precision': 0.06153846153846154, 'recall': 0.4, 'f1': 0.10666666666666667, 'number': 10} |
| | - Overall Precision: 0.0310 |
| | - Overall Recall: 0.1739 |
| | - Overall F1: 0.0526 |
| | - Overall Accuracy: 0.8882 |
| |
|
| | ## 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: 3e-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 |
| | - num_epochs: 2 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Footer | Header | Able | Aption | Ext | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:------------------------------------------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:| |
| | | 2.0796 | 1.0 | 5 | 1.4462 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.05063291139240506, 'recall': 0.4, 'f1': 0.0898876404494382, 'number': 10} | 0.0255 | 0.1739 | 0.0444 | 0.8518 | |
| | | 1.2478 | 2.0 | 10 | 1.1562 | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 1} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 5} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.06153846153846154, 'recall': 0.4, 'f1': 0.10666666666666667, 'number': 10} | 0.0310 | 0.1739 | 0.0526 | 0.8882 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.0 |
| | - Pytorch 1.12.1 |
| | - Datasets 2.9.0 |
| | - Tokenizers 0.13.2 |
| |
|
