update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: punctuation-nilc-bert-large
+  results: []
+---
+
+<!-- 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. -->
+
+# punctuation-nilc-bert-large
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.1585
+- Precision: 0.9053
+- Recall: 0.8923
+- F1: 0.8988
+- Accuracy: 0.9755
+
+## 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: 5e-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: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0742        | 1.0   | 1172 | 0.0653          | 0.9194    | 0.8702 | 0.8941 | 0.9742   |
+| 0.0396        | 2.0   | 2344 | 0.0773          | 0.9088    | 0.8834 | 0.8959 | 0.9748   |
+| 0.0153        | 3.0   | 3516 | 0.1171          | 0.8996    | 0.8817 | 0.8906 | 0.9739   |
+| 0.0059        | 4.0   | 4688 | 0.1390          | 0.9174    | 0.8719 | 0.8941 | 0.9747   |
+| 0.0024        | 5.0   | 5860 | 0.1585          | 0.9053    | 0.8923 | 0.8988 | 0.9755   |
+
+
+### Framework versions
+
+- Transformers 4.24.0
+- Pytorch 1.12.1+cu113
+- Datasets 2.6.1
+- Tokenizers 0.13.2