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Training Complete
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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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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.
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| 0.0413 | 2.0 | 3512 | 0.0567 | 0.9285 | 0.9490 | 0.9387 | 0.9854 |
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| 0.0257 | 3.0 | 5268 | 0.0607 | 0.9336 | 0.9493 | 0.9414 | 0.9861 |
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### Framework versions
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- Transformers 4.
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- Pytorch 2.0
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- Datasets 2.
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- Tokenizers 0.
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metrics:
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- name: Precision
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type: precision
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value: 0.9246958237421901
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- name: Recall
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type: recall
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value: 0.9464826657691013
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- name: F1
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type: f1
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value: 0.9354624085163007
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- name: Accuracy
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type: accuracy
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value: 0.9848855006769883
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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: 0.0684
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- Precision: 0.9247
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- Recall: 0.9465
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- F1: 0.9355
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- Accuracy: 0.9849
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## Model description
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.0356 | 1.0 | 1756 | 0.0684 | 0.9247 | 0.9465 | 0.9355 | 0.9849 |
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### Framework versions
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- Transformers 4.35.2
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- Pytorch 2.1.0+cu118
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- Datasets 2.15.0
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- Tokenizers 0.15.0
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