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LVI_bert-large-portuguese-cased

Text Classification
Transformers
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bert
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  1. README.md +13 -14
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  license: mit
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- base_model: neuralmind/bert-base-portuguese-cased
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  tags:
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  - generated_from_trainer
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  metrics:
@@ -9,22 +9,22 @@ metrics:
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  - precision
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  - recall
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  model-index:
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- - name: LVI_bert-base-portuguese-cased
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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- # LVI_bert-base-portuguese-cased
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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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2393
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- - Accuracy: 0.9428
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- - F1: 0.9445
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- - Precision: 0.9182
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- - Recall: 0.9723
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  ## Model description
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@@ -55,11 +55,10 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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- | 0.1736 | 1.0 | 3217 | 0.1532 | 0.9615 | 0.9618 | 0.955 | 0.9686 |
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- | 0.1105 | 2.0 | 6434 | 0.1464 | 0.9629 | 0.9630 | 0.9582 | 0.9679 |
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- | 0.0984 | 3.0 | 9651 | 0.2067 | 0.9525 | 0.9511 | 0.9786 | 0.9251 |
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- | 0.0996 | 4.0 | 12868 | 0.1873 | 0.9608 | 0.9610 | 0.9569 | 0.9651 |
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- | 0.17 | 5.0 | 16085 | 0.2393 | 0.9428 | 0.9445 | 0.9182 | 0.9723 |
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  ### Framework versions
 
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  ---
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  license: mit
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+ base_model: neuralmind/bert-large-portuguese-cased
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  - precision
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  - recall
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  model-index:
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+ - name: LVI_bert-large-portuguese-cased
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  results: []
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # LVI_bert-large-portuguese-cased
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+ This model is a fine-tuned version of [neuralmind/bert-large-portuguese-cased](https://huggingface.co/neuralmind/bert-large-portuguese-cased) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6945
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+ - Accuracy: 0.5
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+ - F1: 0.0
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+ - Precision: 0.0
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+ - Recall: 0.0
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.2141 | 1.0 | 3217 | 0.2055 | 0.9405 | 0.9423 | 0.9140 | 0.9724 |
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+ | 0.7115 | 2.0 | 6434 | 0.6959 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.7041 | 3.0 | 9651 | 0.6931 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.7056 | 4.0 | 12868 | 0.6945 | 0.5 | 0.0 | 0.0 | 0.0 |
 
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  ### Framework versions
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