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kclee111
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bert-finetuned-ner

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  1. README.md +12 -12
  2. runs/Dec29_08-22-05_LEGION/events.out.tfevents.1735428129.LEGION.24488.0 +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: 0.9357083678541839
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  - name: Recall
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  type: recall
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- value: 0.9503534163581285
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  - name: F1
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  type: f1
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- value: 0.9429740335643316
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  - name: Accuracy
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  type: accuracy
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- value: 0.9865632542532525
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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: 0.0619
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- - Precision: 0.9357
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- - Recall: 0.9504
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- - F1: 0.9430
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- - Accuracy: 0.9866
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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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- | 0.0771 | 1.0 | 1756 | 0.0682 | 0.9056 | 0.9303 | 0.9178 | 0.9804 |
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- | 0.0343 | 2.0 | 3512 | 0.0695 | 0.9244 | 0.9424 | 0.9333 | 0.9847 |
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- | 0.0242 | 3.0 | 5268 | 0.0619 | 0.9357 | 0.9504 | 0.9430 | 0.9866 |
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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: 0.9377696647859276
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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: 0.9443516042780749
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9862983457938423
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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: 0.0630
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+ - Precision: 0.9378
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+ - Recall: 0.9510
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+ - F1: 0.9444
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+ - Accuracy: 0.9863
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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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+ | 0.0764 | 1.0 | 1756 | 0.0679 | 0.9084 | 0.9295 | 0.9188 | 0.9813 |
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+ | 0.0361 | 2.0 | 3512 | 0.0680 | 0.9283 | 0.9429 | 0.9355 | 0.9847 |
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+ | 0.023 | 3.0 | 5268 | 0.0630 | 0.9378 | 0.9510 | 0.9444 | 0.9863 |
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  ### Framework versions
runs/Dec29_08-22-05_LEGION/events.out.tfevents.1735428129.LEGION.24488.0 CHANGED
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