update model card README.md

README.md

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+---
+license: mit
+base_model: neuralmind/bert-base-portuguese-cased
+tags:
+- generated_from_trainer
+datasets:
+- glue-ptpt
+metrics:
+- accuracy
+- f1
+model-index:
+- name: paraphrase-bert-portuguese
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue-ptpt
+      type: glue-ptpt
+      config: mrpc
+      split: validation
+      args: mrpc
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8725490196078431
+    - name: F1
+      type: f1
+      value: 0.9106529209621993
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# paraphrase-bert-portuguese
+
+This model is a fine-tuned version of [neuralmind/bert-base-portuguese-cased](https://huggingface.co/neuralmind/bert-base-portuguese-cased) on the glue-ptpt dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6398
+- Accuracy: 0.8725
+- F1: 0.9107
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.4894        | 1.09  | 500  | 0.3384          | 0.8578   | 0.8945 |
+| 0.2603        | 2.18  | 1000 | 0.5077          | 0.8799   | 0.9130 |
+| 0.1316        | 3.27  | 1500 | 0.6398          | 0.8725   | 0.9107 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.4
+- Tokenizers 0.13.3