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README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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- name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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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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### Framework versions
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- Transformers 4.16.2
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- Pytorch 1.10.
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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metrics:
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- name: Precision
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type: precision
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value: 0.9361244415025649
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- name: Recall
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type: recall
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value: 0.9520363513968361
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- name: F1
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type: f1
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value: 0.9440133500208594
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- name: Accuracy
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type: accuracy
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value: 0.986489668570083
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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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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0642
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- Precision: 0.9361
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- Recall: 0.9520
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- F1: 0.9440
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- Accuracy: 0.9865
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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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| 0.0874 | 1.0 | 1756 | 0.0696 | 0.9177 | 0.9344 | 0.9260 | 0.9818 |
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| 0.0324 | 2.0 | 3512 | 0.0634 | 0.9362 | 0.9490 | 0.9426 | 0.9856 |
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| 0.0226 | 3.0 | 5268 | 0.0642 | 0.9361 | 0.9520 | 0.9440 | 0.9865 |
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### Framework versions
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- Transformers 4.16.2
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- Pytorch 1.10.0a0+0aef44c
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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