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bert-ner-finetuned-pii

Token Classification
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bert
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  1. README.md +11 -13
  2. model.safetensors +1 -1
  3. runs/Feb15_12-49-49_49d33556eb46/events.out.tfevents.1708001409.49d33556eb46.34.0 +2 -2
README.md CHANGED
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  ---
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- license: mit
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- base_model: dslim/bert-base-NER
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  tags:
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  - generated_from_trainer
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  metrics:
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  # bert-ner-finetuned-pii
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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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0019
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- - Precision: 0.7429
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- - Recall: 0.7192
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- - F1: 0.7309
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- - Accuracy: 0.9995
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  ## Model description
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- Model is fine tuned in a PII task in students essays
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  ## Intended uses & limitations
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  ## Training and evaluation data
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- to be updated
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  ## Training procedure
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0023 | 1.0 | 724 | 0.0033 | 0.6791 | 0.4589 | 0.5477 | 0.9992 |
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- | 0.0014 | 2.0 | 1448 | 0.0021 | 0.7218 | 0.6575 | 0.6882 | 0.9994 |
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- | 0.001 | 3.0 | 2172 | 0.0019 | 0.7429 | 0.7192 | 0.7309 | 0.9995 |
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  ### Framework versions
 
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  ---
 
 
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # bert-ner-finetuned-pii
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+ This model was trained from scratch on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0076
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+ - Precision: 0.9427
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+ - Recall: 0.9727
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+ - F1: 0.9575
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+ - Accuracy: 0.9982
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  ## Model description
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+ More information needed
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  ## Intended uses & limitations
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  ## Training and evaluation data
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+ More information needed
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  ## Training procedure
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0105 | 1.0 | 1324 | 0.0132 | 0.8641 | 0.9464 | 0.9033 | 0.9960 |
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+ | 0.0056 | 2.0 | 2648 | 0.0080 | 0.9298 | 0.9643 | 0.9467 | 0.9978 |
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+ | 0.0047 | 3.0 | 3972 | 0.0076 | 0.9427 | 0.9727 | 0.9575 | 0.9982 |
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  ### Framework versions
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