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End of training

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  1. README.md +11 -11
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Precision
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  type: precision
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- value: 0.8682319957946382
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  - name: Recall
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  type: recall
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- value: 0.8773016997167139
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  - name: F1
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  type: f1
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- value: 0.8727432848965213
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  - name: Accuracy
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  type: accuracy
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- value: 0.9722407666630775
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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
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2028
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- - Precision: 0.8682
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- - Recall: 0.8773
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- - F1: 0.8727
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- - Accuracy: 0.9722
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  ## Model description
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@@ -79,8 +79,8 @@ 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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- | 0.0713 | 1.0 | 3922 | 0.2071 | 0.8649 | 0.8704 | 0.8676 | 0.9710 |
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- | 0.0425 | 2.0 | 7844 | 0.2028 | 0.8682 | 0.8773 | 0.8727 | 0.9722 |
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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: 0.8764705882352941
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  - name: Recall
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  type: recall
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+ value: 0.8969546742209632
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  - name: F1
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  type: f1
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+ value: 0.8865943297164859
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  - name: Accuracy
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  type: accuracy
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+ value: 0.975923333692258
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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 [dslim/distilbert-NER](https://huggingface.co/dslim/distilbert-NER) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1908
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+ - Precision: 0.8765
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+ - Recall: 0.8970
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+ - F1: 0.8866
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+ - Accuracy: 0.9759
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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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+ | 0.0568 | 1.0 | 3922 | 0.1877 | 0.8678 | 0.8893 | 0.8785 | 0.9740 |
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+ | 0.0314 | 2.0 | 7844 | 0.1908 | 0.8765 | 0.8970 | 0.8866 | 0.9759 |
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  ### Framework versions
pytorch_model.bin CHANGED
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