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: bert-base-portuguese-fine-tuned-mrpc
+  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: 0.8504901960784313
+    - name: F1
+      type: f1
+      value: 0.8920353982300885
+---
+
+<!-- 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. -->
+
+# bert-base-portuguese-fine-tuned-mrpc
+
+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: 1.2843
+- Accuracy: 0.8505
+- F1: 0.8920
+
+## 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     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| No log        | 1.0   | 459  | 0.6757          | 0.8603   | 0.8966 |
+| 0.2011        | 2.0   | 918  | 0.7120          | 0.8505   | 0.8897 |
+| 0.1215        | 3.0   | 1377 | 0.9679          | 0.8382   | 0.8764 |
+| 0.0901        | 4.0   | 1836 | 1.0548          | 0.8333   | 0.8799 |
+| 0.0478        | 5.0   | 2295 | 1.3125          | 0.8260   | 0.8769 |
+| 0.0312        | 6.0   | 2754 | 1.0122          | 0.8578   | 0.8953 |
+| 0.0309        | 7.0   | 3213 | 1.2197          | 0.8431   | 0.8849 |
+| 0.0095        | 8.0   | 3672 | 1.1705          | 0.8554   | 0.8941 |
+| 0.0076        | 9.0   | 4131 | 1.3132          | 0.8480   | 0.8912 |
+| 0.0014        | 10.0  | 4590 | 1.2843          | 0.8505   | 0.8920 |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.4
+- Tokenizers 0.13.3