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bert-finetuned-ner

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  1. README.md +12 -12
  2. runs/Aug30_09-42-40_DESKTOP-BKS1PK5/events.out.tfevents.1724985771.DESKTOP-BKS1PK5.32632.0 +2 -2
README.md CHANGED
@@ -26,16 +26,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.9312108215110525
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  - name: Recall
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  type: recall
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- value: 0.9500168293503871
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  - name: F1
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  type: f1
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- value: 0.9405198267244252
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  - name: Accuracy
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  type: accuracy
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- value: 0.9861953258374051
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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
@@ -45,11 +45,11 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.0624
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- - Precision: 0.9312
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- - Recall: 0.9500
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- - F1: 0.9405
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- - Accuracy: 0.9862
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  ## Model description
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@@ -80,9 +80,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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- | 0.0757 | 1.0 | 1756 | 0.0666 | 0.9057 | 0.9342 | 0.9197 | 0.9816 |
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- | 0.0344 | 2.0 | 3512 | 0.0656 | 0.9316 | 0.9460 | 0.9387 | 0.9858 |
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- | 0.021 | 3.0 | 5268 | 0.0624 | 0.9312 | 0.9500 | 0.9405 | 0.9862 |
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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: 0.9363711681855841
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  - name: Recall
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  type: recall
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+ value: 0.9510265903736116
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  - name: F1
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  type: f1
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+ value: 0.9436419804625532
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9860334373344322
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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: 0.0682
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+ - Precision: 0.9364
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+ - Recall: 0.9510
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+ - F1: 0.9436
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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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+ | 0.0765 | 1.0 | 1756 | 0.0629 | 0.9146 | 0.9389 | 0.9266 | 0.9830 |
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+ | 0.0344 | 2.0 | 3512 | 0.0717 | 0.9332 | 0.9455 | 0.9393 | 0.9846 |
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+ | 0.0196 | 3.0 | 5268 | 0.0682 | 0.9364 | 0.9510 | 0.9436 | 0.9860 |
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  ### Framework versions
runs/Aug30_09-42-40_DESKTOP-BKS1PK5/events.out.tfevents.1724985771.DESKTOP-BKS1PK5.32632.0 CHANGED
@@ -1,3 +1,3 @@
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