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bert-finetuned-ner

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  1. README.md +12 -12
  2. runs/Sep13_05-18-46_134fc97c76cf/events.out.tfevents.1726204763.134fc97c76cf.594.0 +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: 0.7791907514450868
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  - name: Recall
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  type: recall
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- value: 0.8564167725540025
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  - name: F1
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  type: f1
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- value: 0.8159806295399515
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  - name: Accuracy
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  type: accuracy
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- value: 0.9823540395867049
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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 ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0713
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- - Precision: 0.7792
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- - Recall: 0.8564
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- - F1: 0.8160
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- - Accuracy: 0.9824
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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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- | 0.1175 | 1.0 | 680 | 0.0609 | 0.7252 | 0.8183 | 0.7690 | 0.9815 |
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- | 0.0437 | 2.0 | 1360 | 0.0603 | 0.7489 | 0.8450 | 0.7940 | 0.9821 |
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- | 0.016 | 3.0 | 2040 | 0.0713 | 0.7792 | 0.8564 | 0.8160 | 0.9824 |
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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: 0.7854671280276817
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  - name: Recall
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  type: recall
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+ value: 0.8653113087674714
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  - name: F1
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  type: f1
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+ value: 0.8234582829504232
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  - name: Accuracy
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  type: accuracy
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+ value: 0.98303871529939
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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 ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0692
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+ - Precision: 0.7855
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+ - Recall: 0.8653
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+ - F1: 0.8235
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+ - Accuracy: 0.9830
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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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+ | 0.1165 | 1.0 | 680 | 0.0630 | 0.7403 | 0.8221 | 0.7790 | 0.9813 |
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+ | 0.0429 | 2.0 | 1360 | 0.0617 | 0.7691 | 0.8463 | 0.8058 | 0.9833 |
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+ | 0.0162 | 3.0 | 2040 | 0.0692 | 0.7855 | 0.8653 | 0.8235 | 0.9830 |
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  ### Framework versions
runs/Sep13_05-18-46_134fc97c76cf/events.out.tfevents.1726204763.134fc97c76cf.594.0 CHANGED
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