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README.md
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- generated_from_trainer
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datasets:
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- conll2003
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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-base-NER-finetuned-ner
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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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dataset:
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name: conll2003
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type: conll2003
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args: conll2003
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metrics:
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- name: Precision
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type: precision
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value: 0.9327342290239345
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- name: Recall
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type: recall
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value: 0.9405167773192177
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- name: F1
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type: f1
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value: 0.9366093366093367
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- name: Accuracy
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type: accuracy
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value: 0.9850621063165951
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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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# bert-base-NER-finetuned-ner
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This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0723
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- Precision: 0.9327
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- Recall: 0.9405
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- F1: 0.9366
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- Accuracy: 0.9851
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 3
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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 | 220 | 0.0754 | 0.9225 | 0.9296 | 0.9260 | 0.9831 |
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| No log | 2.0 | 440 | 0.0688 | 0.9319 | 0.9407 | 0.9363 | 0.9849 |
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| 0.0717 | 3.0 | 660 | 0.0723 | 0.9327 | 0.9405 | 0.9366 | 0.9851 |
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### Framework versions
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- Transformers 4.18.0
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- generated_from_trainer
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datasets:
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- conll2003
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model-index:
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- name: bert-base-NER-finetuned-ner
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results: []
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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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# bert-base-NER-finetuned-ner
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This model is a fine-tuned version of [dslim/bert-base-NER](https://huggingface.co/dslim/bert-base-NER) on the conll2003 dataset.
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## Model description
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Framework versions
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- Transformers 4.18.0
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