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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model_index: |
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- name: bert-portuguese-ner-archive |
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results: |
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- task: |
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name: Token Classification |
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type: token-classification |
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metric: |
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name: Accuracy |
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type: accuracy |
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value: 0.9700325118974698 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# bert-portuguese-ner-archive |
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This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1140 |
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- Precision: 0.9147 |
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- Recall: 0.9483 |
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- F1: 0.9312 |
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- Accuracy: 0.9700 |
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## Model description |
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This model was fine-tunned on token classification task (NER) on Portuguese archival documents. The annotated labels are: Date, Profession, Person, Place, Organization |
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### Datasets |
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All the training and evaluation data is available at: http://ner.epl.di.uminho.pt/ |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| No log | 1.0 | 192 | 0.1438 | 0.8917 | 0.9392 | 0.9148 | 0.9633 | |
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| 0.2454 | 2.0 | 384 | 0.1222 | 0.8985 | 0.9417 | 0.9196 | 0.9671 | |
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| 0.0526 | 3.0 | 576 | 0.1098 | 0.9150 | 0.9481 | 0.9312 | 0.9698 | |
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| 0.0372 | 4.0 | 768 | 0.1140 | 0.9147 | 0.9483 | 0.9312 | 0.9700 | |
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### Framework versions |
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- Transformers 4.10.0.dev0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.10.2 |
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- Tokenizers 0.10.3 |
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### Citation |
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@InProceedings{10.1007/978-3-031-04819-7_33, |
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author="da Costa Cunha, Lu{\'i}s Filipe |
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and Ramalho, Jos{\'e} Carlos", |
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editor="Rocha, Alvaro |
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and Adeli, Hojjat |
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and Dzemyda, Gintautas |
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and Moreira, Fernando", |
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title="NER in Archival Finding Aids: Next Level", |
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booktitle="Information Systems and Technologies", |
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year="2022", |
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publisher="Springer International Publishing", |
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address="Cham", |
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pages="333--342", |
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isbn="978-3-031-04819-7" |
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} |
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