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Training complete

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  1. README.md +10 -10
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: bert-base-cased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # bert-finetuned-ner
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- This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0854
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- - Precision: 0.9707
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- - Recall: 0.9773
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- - F1: 0.9740
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- - Accuracy: 0.9845
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0627 | 1.0 | 5285 | 0.1139 | 0.9563 | 0.9675 | 0.9619 | 0.9785 |
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- | 0.0502 | 2.0 | 10570 | 0.0914 | 0.9675 | 0.9744 | 0.9709 | 0.9829 |
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- | 0.0686 | 3.0 | 15855 | 0.0854 | 0.9707 | 0.9773 | 0.9740 | 0.9845 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: albert/albert-base-v1
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # bert-finetuned-ner
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+ This model is a fine-tuned version of [albert/albert-base-v1](https://huggingface.co/albert/albert-base-v1) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0994
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+ - Precision: 0.9628
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+ - Recall: 0.9740
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+ - F1: 0.9683
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+ - Accuracy: 0.9813
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 0.0688 | 1.0 | 5285 | 0.1227 | 0.9555 | 0.9670 | 0.9612 | 0.9769 |
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+ | 0.0583 | 2.0 | 10570 | 0.1051 | 0.9581 | 0.9723 | 0.9652 | 0.9803 |
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+ | 0.0798 | 3.0 | 15855 | 0.0994 | 0.9628 | 0.9740 | 0.9683 | 0.9813 |
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  ### Framework versions