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LVI_bert-base-portuguese-cased

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  1. README.md +21 -15
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,24 +1,30 @@
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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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  - accuracy
 
 
 
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  model-index:
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- - name: LVI-dsl_tl-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-dsl_tl-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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0750
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- - Accuracy: 0.6075
 
 
 
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  ## Model description
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@@ -37,23 +43,23 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 3e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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- - num_epochs: 300
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 1.0 | 217 | 0.8088 | 0.6539 |
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- | No log | 2.0 | 434 | 0.7666 | 0.6660 |
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- | 0.7597 | 3.0 | 651 | 0.9131 | 0.6509 |
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- | 0.7597 | 4.0 | 868 | 0.9328 | 0.6206 |
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- | 0.5046 | 5.0 | 1085 | 1.0750 | 0.6075 |
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  ### Framework versions
 
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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:
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  - accuracy
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+ - f1
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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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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 42
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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+ - num_epochs: 10
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  ### Training results
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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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