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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) 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: 0.9841
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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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metrics:
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- name: Precision
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type: precision
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value: 0.9278601460500111
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- name: Recall
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type: recall
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value: 0.9381362568519969
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- name: F1
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type: f1
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value: 0.9329699059909885
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- name: Accuracy
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type: accuracy
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value: 0.9841295057746994
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0602
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- Precision: 0.9279
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- Recall: 0.9381
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- F1: 0.9330
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- Accuracy: 0.9841
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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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| 0.2379 | 1.0 | 878 | 0.0679 | 0.9193 | 0.9242 | 0.9217 | 0.9818 |
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| 0.0508 | 2.0 | 1756 | 0.0609 | 0.9220 | 0.9355 | 0.9287 | 0.9835 |
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| 0.0306 | 3.0 | 2634 | 0.0602 | 0.9279 | 0.9381 | 0.9330 | 0.9841 |
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### Framework versions
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