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bert-finetuned-ner

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  1. README.md +12 -12
  2. runs/Sep17_05-59-50_041092765f38/events.out.tfevents.1726552793.041092765f38.588.0 +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: 0.8066825775656324
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  - name: Recall
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  type: recall
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- value: 0.8589580686149937
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  - name: F1
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  type: f1
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- value: 0.832
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  - name: Accuracy
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  type: accuracy
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- value: 0.9839353700436438
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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 [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0612
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- - Precision: 0.8067
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- - Recall: 0.8590
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- - F1: 0.832
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- - Accuracy: 0.9839
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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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- | 0.1242 | 1.0 | 680 | 0.0521 | 0.7460 | 0.8399 | 0.7902 | 0.9825 |
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- | 0.039 | 2.0 | 1360 | 0.0515 | 0.7891 | 0.8463 | 0.8167 | 0.9835 |
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- | 0.0144 | 3.0 | 2040 | 0.0612 | 0.8067 | 0.8590 | 0.832 | 0.9839 |
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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: 0.8116805721096544
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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: 0.8376383763837638
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9840282291763395
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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 [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the ncbi_disease dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0621
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+ - Precision: 0.8117
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+ - Recall: 0.8653
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+ - F1: 0.8376
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+ - Accuracy: 0.9840
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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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+ | 0.1181 | 1.0 | 680 | 0.0523 | 0.7339 | 0.8272 | 0.7778 | 0.9824 |
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+ | 0.0386 | 2.0 | 1360 | 0.0554 | 0.8112 | 0.8463 | 0.8284 | 0.9838 |
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+ | 0.0145 | 3.0 | 2040 | 0.0621 | 0.8117 | 0.8653 | 0.8376 | 0.9840 |
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  ### Framework versions
runs/Sep17_05-59-50_041092765f38/events.out.tfevents.1726552793.041092765f38.588.0 CHANGED
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