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Training complete

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  1. README.md +11 -11
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  ---
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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:
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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 the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1718
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- - Precision: 0.8772
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- - Recall: 0.2754
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- - F1: 0.2846
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- - Accuracy: 0.8235
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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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- | No log | 1.0 | 68 | 0.1821 | 0.8035 | 0.2405 | 0.2389 | 0.8162 |
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- | No log | 2.0 | 136 | 0.1837 | 0.8876 | 0.2788 | 0.2806 | 0.8162 |
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- | No log | 3.0 | 204 | 0.1718 | 0.8772 | 0.2754 | 0.2846 | 0.8235 |
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  ### Framework versions
 
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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-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 None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1297
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+ - Precision: 0.8328
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+ - Recall: 0.3864
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+ - F1: 0.3321
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+ - Accuracy: 0.8676
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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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+ | No log | 1.0 | 51 | 0.1687 | 0.6907 | 0.2347 | 0.2279 | 0.8456 |
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+ | No log | 2.0 | 102 | 0.1344 | 0.8467 | 0.3308 | 0.2812 | 0.8603 |
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+ | No log | 3.0 | 153 | 0.1297 | 0.8328 | 0.3864 | 0.3321 | 0.8676 |
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  ### Framework versions