Update README.md

README.md

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-language: "pt"
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 # CardioBERTpt - Portuguese Transformer-based Models for Clinical Language Representation in Cardiology
 
-This model card describes CardioBERTpt, a clinical model trained on the cardiology domain for NER tasks in Portuguese. 
+This model card describes CardioBERTpt, a clinical model trained on the cardiology domain for NER tasks in Portuguese. This model is a fine-tuned version of [bert-base-multilingual-cased](https://huggingface.co/bert-base-multilingual-cased) on a cardiology text dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4495
+- Accuracy: 0.8864
 
 ## How to use the model
 
@@ -15,6 +14,24 @@ tokenizer = AutoTokenizer.from_pretrained("pucpr-br/cardiobertpt")
 model = AutoModel.from_pretrained("pucpr-br/cardiobertpt")
 ```
 
+## Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 15.0
+
+## Framework versions
+
+- Transformers 4.17.0.dev0
+- Pytorch 1.8.0
+- Datasets 1.18.3
+- Tokenizers 0.11.0
+
 ## More Information
 
 Refer to the original paper, [CardioBERTpt - Portuguese Transformer-based Models for Clinical Language Representation in Cardiology](https://ieeexplore.ieee.org/document/10178779/) for additional details and performance on Portuguese NER tasks.