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Model save

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  1. README.md +12 -12
  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: 0.8717564870259481
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  - name: Recall
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  type: recall
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- value: 0.8995880535530381
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  - name: F1
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  type: f1
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- value: 0.88545362392296
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  - name: Accuracy
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  type: accuracy
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- value: 0.9836487420412604
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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 [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the lener_br dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0652
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- - Precision: 0.8718
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- - Recall: 0.8996
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- - F1: 0.8855
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- - Accuracy: 0.9836
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  ## Model description
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@@ -79,9 +79,9 @@ 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 | 490 | 0.0911 | 0.8063 | 0.7703 | 0.7879 | 0.9734 |
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- | 0.1901 | 2.0 | 980 | 0.0665 | 0.8525 | 0.8929 | 0.8722 | 0.9819 |
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- | 0.0419 | 3.0 | 1470 | 0.0652 | 0.8718 | 0.8996 | 0.8855 | 0.9836 |
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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: 0.8649122807017544
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  - name: Recall
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  type: recall
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+ value: 0.8885169927909372
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  - name: F1
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  type: f1
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+ value: 0.8765557531115061
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9821930095431353
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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 [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the lener_br dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0679
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+ - Precision: 0.8649
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+ - Recall: 0.8885
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+ - F1: 0.8766
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+ - Accuracy: 0.9822
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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 | 490 | 0.0795 | 0.8185 | 0.7907 | 0.8043 | 0.9753 |
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+ | 0.1925 | 2.0 | 980 | 0.0683 | 0.8475 | 0.8602 | 0.8538 | 0.9803 |
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+ | 0.0422 | 3.0 | 1470 | 0.0679 | 0.8649 | 0.8885 | 0.8766 | 0.9822 |
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  ### Framework versions
pytorch_model.bin CHANGED
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