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End of training

Browse files
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: 0.25396825396825395
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  - name: Recall
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  type: recall
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- value: 0.013463480309660047
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  - name: F1
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  type: f1
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- value: 0.02557136007671408
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  - name: Accuracy
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  type: accuracy
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- value: 0.832346871227756
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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-large-cased](https://huggingface.co/bert-large-cased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8383
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- - Precision: 0.2540
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- - Recall: 0.0135
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- - F1: 0.0256
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- - Accuracy: 0.8323
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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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- | No log | 1.0 | 10 | 1.1916 | 0.1247 | 0.0533 | 0.0747 | 0.8105 |
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- | No log | 2.0 | 20 | 0.8755 | 0.2004 | 0.0160 | 0.0296 | 0.8307 |
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- | No log | 3.0 | 30 | 0.8383 | 0.2540 | 0.0135 | 0.0256 | 0.8323 |
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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: 0.26426174496644295
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  - name: Recall
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  type: recall
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+ value: 0.05301245371928644
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  - name: F1
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  type: f1
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+ value: 0.08830950378469302
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8491102371402983
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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-large-cased](https://huggingface.co/bert-large-cased) on the conll2003 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5525
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+ - Precision: 0.2643
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+ - Recall: 0.0530
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+ - F1: 0.0883
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+ - Accuracy: 0.8491
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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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+ | No log | 1.0 | 25 | 0.7702 | 0.2857 | 0.0003 | 0.0007 | 0.8326 |
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+ | No log | 2.0 | 50 | 0.6046 | 0.1537 | 0.0106 | 0.0198 | 0.8373 |
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+ | No log | 3.0 | 75 | 0.5525 | 0.2643 | 0.0530 | 0.0883 | 0.8491 |
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  ### Framework versions
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