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bert-finetuned-ner

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bert
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  1. README.md +12 -12
  2. runs/Sep16_23-36-10_0a40eaa23cc0/events.out.tfevents.1726529774.0a40eaa23cc0.443.0 +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: 0.8033573141486811
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  - name: Recall
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  type: recall
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- value: 0.8513341804320204
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  - name: F1
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  type: f1
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- value: 0.8266502159161011
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  - name: Accuracy
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  type: accuracy
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- value: 0.9835329804686291
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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: 0.0626
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- - Precision: 0.8034
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- - Recall: 0.8513
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- - F1: 0.8267
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- - Accuracy: 0.9835
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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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- | 0.1245 | 1.0 | 680 | 0.0536 | 0.7295 | 0.8158 | 0.7702 | 0.9814 |
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- | 0.0392 | 2.0 | 1360 | 0.0551 | 0.7907 | 0.8399 | 0.8145 | 0.9831 |
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- | 0.0155 | 3.0 | 2040 | 0.0626 | 0.8034 | 0.8513 | 0.8267 | 0.9835 |
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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: 0.8066825775656324
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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
 
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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
runs/Sep16_23-36-10_0a40eaa23cc0/events.out.tfevents.1726529774.0a40eaa23cc0.443.0 CHANGED
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