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LVI_albertina-100m-portuguese-ptpt-encoder

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  1. README.md +12 -9
  2. model.safetensors +1 -1
README.md CHANGED
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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:
@@ -9,18 +9,18 @@ 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
@@ -55,10 +55,13 @@ 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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- | 0.2141 | 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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  ---
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  license: mit
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+ base_model: PORTULAN/albertina-100m-portuguese-ptpt-encoder
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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_albertina-100m-portuguese-ptpt-encoder
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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_albertina-100m-portuguese-ptpt-encoder
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+ This model is a fine-tuned version of [PORTULAN/albertina-100m-portuguese-ptpt-encoder](https://huggingface.co/PORTULAN/albertina-100m-portuguese-ptpt-encoder) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6932
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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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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
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+ | 0.5678 | 1.0 | 3217 | 0.6316 | 0.6653 | 0.5619 | 0.8128 | 0.4294 |
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+ | 0.6042 | 2.0 | 6434 | 0.6911 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.6946 | 3.0 | 9651 | 0.6932 | 0.5 | 0.0 | 0.0 | 0.0 |
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+ | 0.694 | 4.0 | 12868 | 0.6932 | 0.5 | 0.6667 | 0.5 | 1.0 |
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+ | 0.6942 | 5.0 | 16085 | 0.6933 | 0.5 | 0.6667 | 0.5 | 1.0 |
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+ | 0.6936 | 6.0 | 19302 | 0.6937 | 0.5 | 0.6667 | 0.5 | 1.0 |
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+ | 0.6937 | 7.0 | 22519 | 0.6932 | 0.5 | 0.0 | 0.0 | 0.0 |
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  ### Framework versions
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