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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- article100v4_wikigold_split
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: Article_100v4_NER_Model_3Epochs_UNAUGMENTED
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results:
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- task:
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name: Token Classification
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type: token-classification
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dataset:
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name: article100v4_wikigold_split
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type: article100v4_wikigold_split
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args: default
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metrics:
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- name: Precision
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type: precision
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value: 0.16216216216216217
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- name: Recall
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type: recall
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value: 0.0030761343245321714
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- name: F1
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type: f1
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value: 0.006037735849056605
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- name: Accuracy
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type: accuracy
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value: 0.7826991539137269
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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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should probably proofread and complete it, then remove this comment. -->
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# Article_100v4_NER_Model_3Epochs_UNAUGMENTED
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the article100v4_wikigold_split dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5862
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- Precision: 0.1622
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- Recall: 0.0031
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- F1: 0.0060
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- Accuracy: 0.7827
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 8
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- eval_batch_size: 8
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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: 3
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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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| No log | 1.0 | 12 | 0.7284 | 0.0 | 0.0 | 0.0 | 0.7816 |
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| No log | 2.0 | 24 | 0.6227 | 0.2 | 0.0003 | 0.0005 | 0.7817 |
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| No log | 3.0 | 36 | 0.5862 | 0.1622 | 0.0031 | 0.0060 | 0.7827 |
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### Framework versions
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- Transformers 4.17.0
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- Pytorch 1.11.0+cu113
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- Datasets 2.4.0
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- Tokenizers 0.11.6
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