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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 4.27.
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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metrics:
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- name: Precision
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type: precision
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value: 0.9343150231634679
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- name: Recall
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type: recall
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value: 0.9503534163581285
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- name: F1
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type: f1
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value: 0.9422659769731353
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- name: Accuracy
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type: accuracy
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value: 0.9859598516512628
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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: 0.0611
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- Precision: 0.9343
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- Recall: 0.9504
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- F1: 0.9423
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- Accuracy: 0.9860
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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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| 0.085 | 1.0 | 1756 | 0.0658 | 0.9169 | 0.9345 | 0.9257 | 0.9827 |
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| 0.0331 | 2.0 | 3512 | 0.0641 | 0.9302 | 0.9493 | 0.9397 | 0.9858 |
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| 0.018 | 3.0 | 5268 | 0.0611 | 0.9343 | 0.9504 | 0.9423 | 0.9860 |
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### Framework versions
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- Transformers 4.27.2
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- Pytorch 1.13.1+cu116
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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